'Not in it for huge profits but because it's right': The contested moral economies of UK-India exports in health worker education and training.

While the growth of global markets in health-related services may have significant consequences for healthcare provisioning and training, it has received relatively little attention from the social sciences. This article examines UK-India, and specifically England-India, exports in health worker education and training as one such global market, drawing on sociological scholarship on moral economies to understand how trading in this field is constructed and legitimated by the individuals and organisations involved, what tensions evolve, and what is at stake in them. We employ a qualitative mixed methods approach using publicly available materials on existing UK-India collaborations and primary data from interviews with key stakeholders in India and the UK, including government departments, arms-length bodies, NHS Trusts, trade associations and private providers. Our analysis illustrates the key discursive strategies used to legitimate engagement in these markets, and the complex and contested moral economies unfolding between and across these stakeholders and contexts. Not least, we demonstrate the conflicting moral sentiments and the boundary work required to realise commodification. Situating cross-border trade in health worker education and training in a moral economy framework thus illuminates the social context and moral worlds in which this evolving trade is embedded.

Radiomics-based decision support tool assists radiologists in small lung nodule classification and improves lung cancer early diagnosis.

BACKGROUND: Methods to improve stratification of small (≤15 mm) lung nodules are needed. We aimed to develop a radiomics model to assist lung cancer diagnosis. METHODS: Patients were retrospectively identified using health records from January 2007 to December 2018. The external test set was obtained from the national LIBRA study and a prospective Lung Cancer Screening programme. Radiomics features were extracted from multi-region CT segmentations using TexLab2.0. LASSO regression generated the 5-feature small nodule radiomics-predictive-vector (SN-RPV). K-means clustering was used to split patients into risk groups according to SN-RPV. Model performance was compared to 6 thoracic radiologists. SN-RPV and radiologist risk groups were combined to generate "Safety-Net" and "Early Diagnosis" decision-support tools. RESULTS: In total, 810 patients with 990 nodules were included. The AUC for malignancy prediction was 0.85 (95% CI: 0.82-0.87), 0.78 (95% CI: 0.70-0.85) and 0.78 (95% CI: 0.59-0.92) for the training, test and external test datasets, respectively. The test set accuracy was 73% (95% CI: 65-81%) and resulted in 66.67% improvements in potentially missed [8/12] or delayed [6/9] cancers, compared to the radiologist with performance closest to the mean of six readers. CONCLUSIONS: SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.

A highly sensitive LC-MS/MS method for quantitative determination of 7 vitamin D metabolites in mouse brain tissue.

Despite its critical role in neurodevelopment and brain function, vitamin D (vit-D) homeostasis, metabolism, and kinetics within the central nervous system remain largely undetermined. Thus, it is of critical importance to establish an accurate, highly sensitive, and reproducible method to quantitate vit-D in brain tissue. Here, we present a novel liquid chromatography tandem mass spectrometry (LC-MS/MS) method and for the first time, demonstrate detection of seven major vit-D metabolites in brain tissues of C57BL/6J wild-type mice, namely 1,25(OH)2D3, 3-epi-1,25(OH)2D3, 1,25(OH)2D2, 25(OH)D3, 25(OH)D2, 24,25(OH)2D3, and 24,25(OH)2D2. Chromatographic separation was achieved on a pentaflurophenyl column with 3 mM ammonium formate water/methanol [A] and 3 mM ammonium formate methanol/isopropanol [B] mobile phase components. Detection was by positive ion electrospray tandem mass spectrometry with the EVOQ elite triple quadrupole mass spectrometer with an Advance ultra-high-performance liquid chromatograph and online extraction system. Calibration standards of each metabolite prepared in brain matrices were used to validate the detection range, precision, accuracy, and recovery. Isotopically labelled analogues, 1,25(OH)2D3-d3, 25(OH)D3-c5, and 24,25(OH)2D3-d6, served as the internal standards for the closest molecular-related metabolite in all measurements. Standards between 1 fg/mL and 10 ng/mL were injected with a resulting linear range between 0.001 and 1 ng, with an LLOD and LLOQ of 1 pg/mL and 12.5 pg/mL, respectively. The intra-/inter-day precision and accuracy for measuring brain vit-D metabolites ranged between 0.12-11.53% and 0.28-9.11%, respectively. Recovery in acetonitrile ranged between 99.09 and 106.92% for all metabolites. Collectively, the sensitivity and efficiency of our method supersedes previously reported protocols used to measure vit-D and to our knowledge, the first protocol to reveal the abundance of 25(OH)D2, 1,25(OH)D2, and 24,25(OH)2D2, in brain tissue of any species. This technique may be important in supporting the future advancement of pre-clinical research into the function of vit-D in neurophysiological and neuropsychiatric disorders, and neurodegeneration.

Constructing healthcare services markets: networks, brokers and the China-England engagement.

BACKGROUND: Healthcare services is an expanding international market with which national healthcare systems engage, and from which they benefit, to greater and lesser degrees. This study examines the case of the China-England engagement in healthcare services as a vehicle for illuminating the way in which such market relationships are constructed. FINDINGS: China and England have different approaches to the international healthcare services market. Aware of the knowledge and technology gaps between itself and the leading capitalist nations of the West in healthcare, as in other sectors, the Chinese leadership has encouraged a variety of international engagements to facilitate the bridging of these gaps including accessing new supply and demand relationships in international markets. These engagements are situated within an approach to health system development based on establishing broad policy directions, allowing a degree of local innovation, initiating and evaluating pilot studies, and promulgating new programmatic frameworks at central and local levels. The assumption is that the new knowledge and technologies are integrated into this approach and implemented under the guidance of Chinese experts and leaders. England's healthcare system has the knowledge resources to provide the supply to meet at least some of the China demand but has yet to develop fully the means to enable an efficient market response, though such economic engagement is supported by the UK's trade related departments of state. As a result, the development of China-England commercial relationships in patient care, professional education and hospital and healthcare service development has been led largely by high status NHS Trusts and private sector organisations with the entrepreneurial capacity to exploit their market position. Drawing on their established international clinicians and commercial teams with experience of domestic private sector provision, these institutions have built trust-based collaborations sufficiently robust to facilitate demand-supply relationships in the international healthcare services market. Often key to the development of relations required to make commercial exchange feasible and practicable are a range of international brokers with the skills and capacity to provide the necessary linkage with individual healthcare consumers and institutional clients in China. Integral to the broker role, and often supplied by the broker itself, are the communication technologies of telemedicine to enable the interaction between consumer and healthcare provider, be this in patient care, professional education or healthcare service development. CONCLUSIONS: Although England's healthcare system has the knowledge required to respond to China's market demand and such economic engagement is supported and actively encouraged by the UK's trade related departments of state, the response is constrained by multiple domestic demands on its resources and by the limits of the NHS approach to marketisation in healthcare.

Decentred regulation: The case of private healthcare in India.

In order to progress towards more equitable social welfare systems we need an improved understanding of regulation in social sectors such as health and education. However, research to date has tended to focus on roles for governments and professions, overlooking the broader range of regulatory systems that emerge in contexts of market-based provisioning and partial state regulation. In this article we examine the regulation of private healthcare in India using an analytical approach informed by 'decentred' and 'regulatory capitalism' perspectives. We apply these ideas to qualitative data on private healthcare and its regulation in Maharashtra (review of press media, semi-structured interviews with 43 respondents, and three witness seminars), in order to describe the range of state and non-state actors involved in setting rules and norms in this context, whose interests are represented by these activities, and what problems arise. We show an eclectic set of regulatory systems in operation. Government and statutory councils do perform limited and sporadic regulatory roles, typically organised around legislation, licensing and inspections, and often prompted by the judicial arm of the state. But a range of industry-level actors, private organisations and public insurers are involved too, promoting their own interests in the sector via the offices of regulatory capitalism: accreditation companies, insurers, platform operators and consumer courts. Rules and norms are extensive but diffuse. These are produced not just through laws, licensing and professional codes of conduct, but also through industry influence over standards, practices and market organisation, and through individualised attempts to negotiate exceptions and redressal. Our findings demonstrate regulation in a marketised social sector to be partial, disjointed and decentred to multiple loci, actively representing differing interests. Greater understanding of the different actors and processes at play in such contexts can inform future progress towards universal systems for social welfare.

Going for brokerage: strategies and strains in commercial healthcare facilitation.

BACKGROUND: The formation of domestic and global marketplaces during the past 50 years has opened up new commercial opportunities for third-party activity in healthcare systems. Commercial mediation of access to healthcare is one recent area of activity that sees companies and individuals offering to organise healthcare and travel in return for payment. With varying degrees of control over the location, type, cost and experiences of healthcare provisioning, these intermediaries occupy potentially influential positions in healthcare systems and yet much of their work is poorly understood. METHODS: Drawing on social science theories of brokerage, this article presents a novel analysis of commercial healthcare facilitation. It focuses on facilitation companies and their workers as central, intermediating actors for people to access healthcare in markets characterised by complexity. Semi-structured interviews were conducted with people working in domestic and international healthcare facilitation in London and Delhi, and data were analysed using a framework approach that emphasises the structural features and personal agencies for this area of work. RESULTS: Findings point to an institutional environment for commercial healthcare facilitation marked by competition and the threat of obsolescence. The activities of rivals, and the risk that users and providers will bypass intermediaries, compels facilitation companies to respond strategically and to continuously pursue new populations and activities to mediate - to go for broke. These pressures percolate into the lives of people who perform facilitation work and who describe a physical and mental burden of labour incurred by onerous processes for generating and completing facilitation work. The need for language interpretation services introduces an additional set of relations and has created further points of tension. It is an environment that engenders mistrust and anxiety, and which incentivises exploitation and a commodification of users whose associated commissions are highly prized. CONCLUSION: Brokerage analysis provides valuable insights into the strategies and strains for commercial mediation of access to healthcare, and the findings indicate opportunities for further research on the contributions of interpreters, diplomatic and business networks, and new technologies, and on the growth of new forms of mediation in domestic and overseas settings.

Demand-side financing for maternal and newborn health: what do we know about factors that affect implementation of cash transfers and voucher programmes?

BACKGROUND: Demand-side financing (DSF) interventions, including cash transfers and vouchers, have been introduced to promote maternal and newborn health in a range of low- and middle-income countries. These interventions vary in design but have typically been used to increase health service utilisation by offsetting some financial costs for users, or increasing household income and incentivising 'healthy behaviours'. This article documents experiences and implementation factors associated with use of DSF in maternal and newborn health. METHODS: A secondary analysis (using an adapted Supporting the Use of Research Evidence framework - SURE) was performed on studies that had previously been identified in a systematic review of evidence on DSF interventions in maternal and newborn health. RESULTS: The article draws on findings from 49 quantitative and 49 qualitative studies. The studies give insights on difficulties with exclusion of migrants, young and multiparous women, with demands for informal fees at facilities, and with challenges maintaining quality of care under increasing demand. Schemes experienced difficulties if communities faced long distances to reach participating facilities and poor access to transport, and where there was inadequate health infrastructure and human resources, shortages of medicines and problems with corruption. Studies that documented improved care-seeking indicated the importance of adequate programme scope (in terms of programme eligibility, size and timing of payments and voucher entitlements) to address the issue of concern, concurrent investments in supply-side capacity to sustain and/or improve quality of care, and awareness generation using community-based workers, leaders and women's groups. CONCLUSIONS: Evaluations spanning more than 15 years of implementation of DSF programmes reveal a complex picture of experiences that reflect the importance of financial and other social, geographical and health systems factors as barriers to accessing care. Careful design of DSF programmes as part of broader maternal and newborn health initiatives would need to take into account these barriers, the behaviours of staff and the quality of care in health facilities. Research is still needed on the policy context for DSF schemes in order to understand how they become sustainable and where they fit, or do not fit, with plans to achieve equitable universal health coverage.

Effects of demand-side financing on utilisation, experiences and outcomes of maternity care in low- and middle-income countries: a systematic review.

BACKGROUND: Demand-side financing, where funds for specific services are channelled through, or to, prospective users, is now employed in health and education sectors in many low- and middle-income countries. This systematic review aimed to critically examine the evidence on application of this approach to promote maternal health in these settings. Five modes were considered: unconditional cash transfers, conditional cash transfers, short-term payments to offset costs of accessing maternity services, vouchers for maternity services, and vouchers for merit goods. We sought to assess the effects of these interventions on utilisation of maternity services and on maternal health outcomes and infant health, the situation of underprivileged women and the healthcare system. METHODS: The protocol aimed for collection and synthesis of a broad range of evidence from quantitative, qualitative and economic studies. Nineteen health and social policy databases, seven unpublished research databases and 27 websites were searched; with additional searches of Indian journals and websites. Studies were included if they examined demand-side financing interventions to increase consumption of services or goods intended to impact on maternal health, and met relevant quality criteria. Quality assessment, data extraction and analysis used Joanna Briggs Institute standardised tools and software. Outcomes of interest included maternal and infant mortality and morbidity, service utilisation, factors required for successful implementation, recipient and provider experiences, ethical issues, and cost-effectiveness. Findings on Effectiveness, Feasibility, Appropriateness and Meaningfulness were presented by narrative synthesis. RESULTS: Thirty-three quantitative studies, 46 qualitative studies, and four economic studies from 17 countries met the inclusion criteria. Evidence on unconditional cash transfers was scanty. Other demand-side financing modes were found to increase utilisation of maternal healthcare in the index pregnancy or uptake of related merit goods. Evidence of effects on maternal and infant mortality and morbidity outcomes was insufficient. Important implementation aspects include targeting and eligibility criteria, monitoring, respectful treatment of beneficiaries, suitable incentives for providers, quality of care and affordable referral systems. CONCLUSIONS: Demand-side financing schemes can increase utilisation of maternity services, but attention must be paid to supply-side conditions, the fine-grain of implementation and sustainability. Comparative studies and research on health impact and cost-effectiveness are required.

National health policy-makers' views on the clarity and utility of Countdown to 2015 country profiles and reports: findings from two exploratory qualitative studies.

BACKGROUND: The use of sets of indicators to assess progress has become commonplace in the global health arena. Exploratory research has suggested that indicators used for global monitoring purposes can play a role in national policy-making, however, the mechanisms through which this occurs are poorly understood. This article reports findings from two qualitative studies that aimed to explore national policy-makers' interpretation and use of indicators from country profiles and reports developed by Countdown to 2015. METHODS: An initial study aimed at exploring comprehension of Countdown data was conducted at the 2010 joint Women Deliver/Countdown conference. A second study was conducted at the 64th World Health Assembly in 2011, specifically targeting national policy-makers. Semi-structured interviews were carried out with 29 and 22 participants, respectively, at each event. Participants were asked about their understanding of specific graphs and indicators used or proposed for use in Countdown country profiles, and their perception of how such data can inform national policy-making. Responses were categorised using a framework analysis. RESULTS: Respondents in both studies acknowledged the importance of the profiles for tracking progress on key health indicators in and across countries, noting that they could be used to highlight changes in coverage, possible directions for future policy, for lobbying finance ministers to increase resources for health, and to stimulate competition between neighbouring or socioeconomically similar countries. However, some respondents raised questions about discrepancies between global estimates and data produced by national governments, and some struggled to understand the profile graphs shown in the absence of explanatory text. Some respondents reported that use of Countdown data in national policy-making was constrained by limited awareness of the initiative, insufficient detail in the country profiles to inform policy, and the absence of indicators felt to be more appropriate to their own country contexts. CONCLUSIONS: The two studies emphasise the need for country consultations to ensure that national policy-makers understand how to interpret and use tools like the Countdown profile for planning purposes. They make clear the value of qualitative research for refining tools used to promote accountability, and the need for country level Countdown-like processes.

Market making and the production of nurses for export: a case study of India-UK health worker migration.

BACKGROUND: High-income countries increasingly look to the international recruitment of health workers to address domestic shortages, especially from low-income and middle-income countries. We adapt conceptual frameworks from migration studies to examine the networked and commercialised nature of the Indian market for nurse migration to the UK. METHODS: We draw on data from 27 expert interviews conducted with migration intermediaries, healthcare providers and policymakers in India and the UK. FINDINGS: India-UK nurse migration occurs within a complex and evolving market encompassing ways to educate, train and recruit nursing candidates. For-profit actors shape the international orientation of nursing curricula, broker on-the-job training and offer language, exam and specialised clinical training. Rather than merely facilitate travel, these brokers produce both generic, emigratory nurses as well as more customised nurses ready to meet specific shortages in the UK. DISCUSSION: The dialectic of producing emigratory and customised nurses is similar to that seen in the Post-Fordist manufacturing model characterised by flexible specialisation and a networked structure. As the commodity in this case are people attempting to improve their position in life, these markets require attention from health policy makers. Nurse production regimes based on international market opportunities are liable to change, subjecting nurses to the risk of having trained for a market that can no longer accommodate them. The commercial nature of activities further entrenches existing socioeconomic inequalities in the Indian nurse force. Negative repercussions for the source healthcare system can be anticipated as highly qualified, specialised nurses leave to work in healthcare systems abroad.

Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis.

BACKGROUND: Pneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) radiation pneumonitis (RP), and infective pneumonitis (IP) is crucial for swift, appropriate, and tailored management to achieve optimal patient outcomes. However, correct diagnosis is often challenging, owing to overlapping clinical presentations and radiological patterns. METHODS: In this multi-centre study of 455 patients, we used machine learning with radiomic features extracted from chest CT imaging to develop and validate five models to distinguish CIP and RP from COVID-19, non-COVID-19 infective pneumonitis, and each other. Model performance was compared to that of two radiologists. RESULTS: Models to distinguish RP from COVID-19, CIP from COVID-19 and CIP from non-COVID-19 IP out-performed radiologists (test set AUCs of 0.92 vs 0.8 and 0.8; 0.68 vs 0.43 and 0.4; 0.71 vs 0.55 and 0.63 respectively). Models to distinguish RP from non-COVID-19 IP and CIP from RP were not superior to radiologists but demonstrated modest performance, with test set AUCs of 0.81 and 0.8 respectively. The CIP vs RP model performed less well on patients with prior exposure to both ICI and radiotherapy (AUC 0.54), though the radiologists also had difficulty distinguishing this test cohort (AUC values 0.6 and 0.6). CONCLUSION: Our results demonstrate the potential utility of such tools as a second or concurrent reader to support oncologists, radiologists, and chest physicians in cases of diagnostic uncertainty. Further research is required for patients with exposure to both ICI and thoracic radiotherapy.

Genome-wide RNA-seq analysis of human and mouse platelet transcriptomes.

Inbred mice are a useful tool for studying the in vivo functions of platelets. Nonetheless, the mRNA signature of mouse platelets is not known. Here, we use paired-end next-generation RNA sequencing (RNA-seq) to characterize the polyadenylated transcriptomes of human and mouse platelets. We report that RNA-seq provides unprecedented resolution of mRNAs that are expressed across the entire human and mouse genomes. Transcript expression and abundance are often conserved between the 2 species. Several mRNAs, however, are differentially expressed in human and mouse platelets. Moreover, previously described functional disparities between mouse and human platelets are reflected in differences at the transcript level, including protease activated receptor-1, protease activated receptor-3, platelet activating factor receptor, and factor V. This suggests that RNA-seq is a useful tool for predicting differences in platelet function between mice and humans. Our next-generation sequencing analysis provides new insights into the human and murine platelet transcriptomes. The sequencing dataset will be useful in the design of mouse models of hemostasis and a catalyst for discovery of new functions of platelets. Access to the dataset is found in the "Introduction."

Non-contrast CT synthesis using patch-based cycle-consistent generative adversarial network (Cycle-GAN) for radiomics and deep learning in the era of COVID-19.

Handcrafted and deep learning (DL) radiomics are popular techniques used to develop computed tomography (CT) imaging-based artificial intelligence models for COVID-19 research. However, contrast heterogeneity from real-world datasets may impair model performance. Contrast-homogenous datasets present a potential solution. We developed a 3D patch-based cycle-consistent generative adversarial network (cycle-GAN) to synthesize non-contrast images from contrast CTs, as a data homogenization tool. We used a multi-centre dataset of 2078 scans from 1,650 patients with COVID-19. Few studies have previously evaluated GAN-generated images with handcrafted radiomics, DL and human assessment tasks. We evaluated the performance of our cycle-GAN with these three approaches. In a modified Turing-test, human experts identified synthetic vs acquired images, with a false positive rate of 67% and Fleiss' Kappa 0.06, attesting to the photorealism of the synthetic images. However, on testing performance of machine learning classifiers with radiomic features, performance decreased with use of synthetic images. Marked percentage difference was noted in feature values between pre- and post-GAN non-contrast images. With DL classification, deterioration in performance was observed with synthetic images. Our results show that whilst GANs can produce images sufficient to pass human assessment, caution is advised before GAN-synthesized images are used in medical imaging applications.

Weak Relationships Between Psychological Factors and Experimental Pain Outcomes in Pain-Free Individuals: An Aggregate Analysis of 8 Studies.

Although psychological factors such as anxiety, depression, and pain catastrophizing are known to influence pain outcomes in chronic pain populations, there are mixed results regarding whether they influence experimental pain outcomes in pain-free individuals. The objectives of this study were to determine the associations between psychological factors and experimental pain outcomes in pain-free adolescents and adults. Relationships between anxiety, depression, and pain catastrophizing and experimental pain outcomes across 8 different studies (total N = 595) were examined in different populations of pain-free adult and adolescent participants. Analyses were conducted with and without controlling for sex, age, and race. Studies were analyzed separately and as part of an aggregate analysis. Individual study analyses resulted in 136 regression models. Of these, only 8 models revealed a significant association between psychological factors and pain outcomes. The significant results were small and likely due to Type 1 error. Controlling for demographic factors had minimal effect on the results. The aggregate analyses revealed weak relationships between anxiety and pressure pain threshold (Fisher's z = -.10 [-.19, -.01]), anxiety and cold pain intensity ratings (Fisher's z = .18 [.04, .32]), and pain catastrophizing and pressure pain threshold (Fisher's z = -.14 [-.26, -.02]). Sample size calculations based on the aggregate analyses indicated that several hundred participants would be required to detect true relationships between these psychological factors and pain measures. The overall negative findings suggest that in pain-free individuals, anxiety, depression, and pain catastrophizing are not meaningfully related to experimental pain outcomes. PERSPECTIVE: Psychological variables have been shown to predict pain outcomes in chronic pain populations but these relationships may not generalize to pain-free populations. An analysis of 595 pain-free individuals across 8 studies in our lab revealed that anxiety, depression, and pain catastrophizing were not meaningfully related to experimental pain outcomes.

Camera-based automated monitoring of flying insects in the wild (Camfi). II. flight behaviour and long-term population monitoring of migratory Bogong moths in Alpine Australia.

Introduction: The Bogong moth Agrotis infusa is well known for its remarkable annual round-trip migration from its breeding grounds across eastern and southern Australia to its aestivation sites in the Australian Alps, to which it provides an important annual influx of nutrients. Over recent years, we have benefited from a growing understanding of the navigational abilities of the Bogong moth. Meanwhile, the population of Bogong moths has been shrinking. Recently, the ecologically and culturally important Bogong moth was listed as endangered by the IUCN Red List, and the establishment of a program for long-term monitoring of its population has been identified as critical for its conservation. Methods: Here, we present the results of two years of monitoring of the Bogong moth population in the Australian Alps using recently developed methods for automated wildlife-camera monitoring of flying insects, named Camfi. While in the Alps, some moths emerge from the caves in the evening to undertake seemingly random flights, filling the air with densities in the dozens per cubic metre. The purpose of these flights is unknown, but they may serve an important role in Bogong moth navigation. Results: We found that these evening flights occur throughout summer and are modulated by daily weather factors. We present a simple heuristic model of the arrival to and departure from aestivation sites by Bogong moths, and confirm results obtained from fox-scat surveys which found that aestivating Bogong moths occupy higher elevations as the summer progresses. Moreover, by placing cameras along two elevational transects below the summit of Mt. Kosciuszko, we found that evening flights were not random, but were systematically oriented in directions relative to the azimuth of the summit of the mountain. Finally, we present the first recorded observations of the impact of bushfire smoke on aestivating Bogong moths - a dramatic reduction in the size of a cluster of aestivating Bogong moths during the fire, and evidence of a large departure from the fire-affected area the day after the fire. Discussion: Our results highlight the challenges of monitoring Bogong moths in the wild and support the continued use of automated camera-based methods for that purpose.

Emerging infectious diseases in southeast Asia: regional challenges to control.

Southeast Asia is a hotspot for emerging infectious diseases, including those with pandemic potential. Emerging infectious diseases have exacted heavy public health and economic tolls. Severe acute respiratory syndrome rapidly decimated the region's tourist industry. Influenza A H5N1 has had a profound effect on the poultry industry. The reasons why southeast Asia is at risk from emerging infectious diseases are complex. The region is home to dynamic systems in which biological, social, ecological, and technological processes interconnect in ways that enable microbes to exploit new ecological niches. These processes include population growth and movement, urbanisation, changes in food production, agriculture and land use, water and sanitation, and the effect of health systems through generation of drug resistance. Southeast Asia is home to about 600 million people residing in countries as diverse as Singapore, a city state with a gross domestic product (GDP) of US$37,500 per head, and Laos, until recently an overwhelmingly rural economy, with a GDP of US$890 per head. The regional challenges in control of emerging infectious diseases are formidable and range from influencing the factors that drive disease emergence, to making surveillance systems fit for purpose, and ensuring that regional governance mechanisms work effectively to improve control interventions.

The Role of Artificial Intelligence in Early Cancer Diagnosis.

Improving the proportion of patients diagnosed with early-stage cancer is a key priority of the World Health Organisation. In many tumour groups, screening programmes have led to improvements in survival, but patient selection and risk stratification are key challenges. In addition, there are concerns about limited diagnostic workforces, particularly in light of the COVID-19 pandemic, placing a strain on pathology and radiology services. In this review, we discuss how artificial intelligence algorithms could assist clinicians in (1) screening asymptomatic patients at risk of cancer, (2) investigating and triaging symptomatic patients, and (3) more effectively diagnosing cancer recurrence. We provide an overview of the main artificial intelligence approaches, including historical models such as logistic regression, as well as deep learning and neural networks, and highlight their early diagnosis applications. Many data types are suitable for computational analysis, including electronic healthcare records, diagnostic images, pathology slides and peripheral blood, and we provide examples of how these data can be utilised to diagnose cancer. We also discuss the potential clinical implications for artificial intelligence algorithms, including an overview of models currently used in clinical practice. Finally, we discuss the potential limitations and pitfalls, including ethical concerns, resource demands, data security and reporting standards.

A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models.

BACKGROUND: Surveillance is universally recommended for non-small cell lung cancer (NSCLC) patients treated with curative-intent radiotherapy. High-quality evidence to inform optimal surveillance strategies is lacking. Machine learning demonstrates promise in accurate outcome prediction for a variety of health conditions. The purpose of this study was to utilise readily available patient, tumour, and treatment data to develop, validate and externally test machine learning models for predicting recurrence, recurrence-free survival (RFS) and overall survival (OS) at 2 years from treatment. METHODS: A retrospective, multicentre study of patients receiving curative-intent radiotherapy for NSCLC was undertaken. A total of 657 patients from 5 hospitals were eligible for inclusion. Data pre-processing derived 34 features for predictive modelling. Combinations of 8 feature reduction methods and 10 machine learning classification algorithms were compared, producing risk-stratification models for predicting recurrence, RFS and OS. Models were compared with 10-fold cross validation and an external test set and benchmarked against TNM-stage and performance status. Youden Index was derived from validation set ROC curves to distinguish high and low risk groups and Kaplan-Meier analyses performed. FINDINGS: Median follow-up time was 852 days. Parameters were well matched across training-validation and external test sets: Mean age was 73 and 71 respectively, and recurrence, RFS and OS rates at 2 years were 43% vs 34%, 54% vs 47% and 54% vs 47% respectively. The respective validation and test set AUCs were as follows: 1) RFS: 0·682 (0·575-0·788) and 0·681 (0·597-0·766), 2) Recurrence: 0·687 (0·582-0·793) and 0·722 (0·635-0·81), and 3) OS: 0·759 (0·663-0·855) and 0·717 (0·634-0·8). Our models were superior to TNM stage and performance status in predicting recurrence and OS. INTERPRETATION: This robust and ready to use machine learning method, validated and externally tested, sets the stage for future clinical trials entailing quantitative personalised risk-stratification and surveillance following curative-intent radiotherapy for NSCLC. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.