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2.
Sci Rep ; 11(1): 17744, 2021 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-34493760

RESUMO

A simple method is utilised to study and compare COVID-19 infection dynamics between countries based on curve fitting to publicly shared data of confirmed COVID-19 infections. The method was tested using data from 80 countries from 6 continents. We found that Johnson cumulative density functions (CDFs) were extremely well fitted to the data (R2 > 0.99) and that Johnson CDFs were much better fitted to the tails of the data than either the commonly used normal or lognormal CDFs. Fitted Johnson CDFs can be used to obtain basic parameters of the infection wave, such as the percentage of the population infected during an infection wave, the days of the start, peak and end of the infection wave, and the duration of the wave's increase and decrease. These parameters can be easily interpreted biologically and used both for describing infection wave dynamics and in further statistical analysis. The usefulness of the parameters obtained was analysed with respect to the relation between the gross domestic product (GDP) per capita, the population density, the percentage of the population infected during an infection wave, the starting day and the duration of the infection wave in the 80 countries. We found that all the above parameters were significantly associated with GDP per capita, but only the percentage of the population infected was significantly associated with population density. If used with caution, this method has a limited ability to predict the future trajectory and parameters of an ongoing infection wave.


Assuntos
COVID-19/epidemiologia , Previsões/métodos , Modelos Estatísticos , Pandemias/estatística & dados numéricos , Interpretação Estatística de Dados , Estudos de Viabilidade , Carga Global da Doença , Produto Interno Bruto/estatística & dados numéricos , Humanos , Distribuição Normal , Densidade Demográfica
3.
Sensors (Basel) ; 21(17)2021 Aug 31.
Artigo em Inglês | MEDLINE | ID: mdl-34502755

RESUMO

Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring individuals' motions in fall risk assessment tasks. Previous SFRA reviews recommend methodological improvements to better support the use of SFRA in clinical practice. This systematic review aimed to investigate the existing evidence of SFRA (discriminative capability, classification performance) and methodological factors (study design, samples, sensor features, and model validation) contributing to the risk of bias. The review was conducted according to recommended guidelines and 33 of 389 screened records were eligible for inclusion. Evidence of SFRA was identified: several sensor features and three classification models differed significantly between groups with different fall risk (mostly fallers/non-fallers). Moreover, classification performance corresponding the AUCs of at least 0.74 and/or accuracies of at least 84% were obtained from sensor features in six studies and from classification models in seven studies. Specificity was at least as high as sensitivity among studies reporting both values. Insufficient use of prospective design, small sample size, low in-sample inclusion of participants with elevated fall risk, high amounts and low degree of consensus in used features, and limited use of recommended model validation methods were identified in the included studies. Hence, future SFRA research should further reduce risk of bias by continuously improving methodology.


Assuntos
Acidentes por Quedas , Dispositivos Eletrônicos Vestíveis , Acidentes por Quedas/prevenção & controle , Idoso , Previsões , Humanos , Estudos Prospectivos
4.
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi ; 33(4): 359-364, 2021 Aug 30.
Artigo em Chinês | MEDLINE | ID: mdl-34505442

RESUMO

OBJECTIVE: To evaluate the impact of environmental and climatic factors on the distribution of suitable habitats of Haemaphysalis longicornis, and to predict the potential distribution of H. longicornis under different climate patterns in China. METHODS: Data pertaining to the distribution of H. longicornis were retrieved from public literatures. The effects of 19 climatic factors (annual mean temperature, annual mean temperature difference between day and night, isothermality, standard deviation of seasonal variation of temperature, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest season, mean temperature of the driest season, mean temperature of the warmest season, mean temperature of the coldest season, annual mean precipitation, precipitation of the wettest month, precipitation of the driest month, coefficient of variance of precipitation, precipitation of the wettest season, precipitation of the driest season, precipitation of the warmest season and precipitation of the coldest season) and 4 environmental factors (elevation, slope, slope aspect and vegetation coverage) on the potential distribution of H. longicornis were assessed using the maximum entropy (MaxEnt) model based on the H. longicornis distribution data and climatic and environmental data, and the potential distribution of H. longicornis was predicted under the RCP 2.6 and 8.5 emissions scenarios. RESULTS: Among the environmental and climatic factors affecting the geographical distribution of H. longicornis in China, the factors contributing more than 10% to the distribution of H. longicornis mainly included the precipitation of the driest month (26.0%), annual mean temperature (11.2%), annual mean precipitation (10.0%) and elevation (24.2%). Under the current climate pattern, the high-, medium- and low-suitable habitats of H. longicornis are 1 231 900, 1 696 200 km2 and 1 854 400 km2 in China, respectively. The distribution of H. longicornis increased by 336 100 km2 and 367 300 km2 in 2050 and 2070 under the RCP 2.6 emissions scenario, and increased by 381 000 km2 and 358 000 km2 in 2050 and 2070 under the RCP 8.5 emissions scenario in China, respectively. CONCLUSIONS: Climatic and environmental factors, such as precipitation, temperature and elevation, greatly affect the distribution of H. longicornis in China, and the suitable habitats of H. longicornis may expand in China under different climate patterns in future.


Assuntos
Mudança Climática , Ecossistema , China , Clima , Previsões , Temperatura
5.
Environ Monit Assess ; 193(10): 622, 2021 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-34477984

RESUMO

In this study, monthly particulate matter (PM2.5) of Paris for the period between January 2000 and December 2019 is investigated by utilizing a periodogram-based time series methodology. The main contribution of the study is modeling the PM2.5 of Paris by extracting the information purely from the examined time series data, where proposed model implicitly captures the effects of other factors, as all their periodic and seasonal effects reside in the air pollution data. Periodicity can be defined as the patterns embedded in the data other than seasonality, and it is crucial to understand the underlying periodic dynamics of air pollutants to better fight pollution. The method we use successfully captures and accounts for the periodicities, which could otherwise be mixed with seasonality under an alternative methodology. Upon the unit root test based on periodograms, it is revealed that the investigated data has periodicities of 1 year and 20 years, so harmonic regression is utilized as an alternative to Box-Jenkins methodology. As the harmonic regression displayed a better performance both in and out-of-sample forecasts, it can be considered as a powerful alternative to model and forecast time series with a periodic structure.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Monitoramento Ambiental , Previsões , Material Particulado/análise
6.
Bone Joint J ; 103-B(9): 1488-1496, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34465149

RESUMO

AIMS: The current study aimed to compare robotic arm-assisted (RA-THA), computer-assisted (CA-THA), and manual (M-THA) total hip arthroplasty regarding in-hospital metrics including length of stay (LOS), discharge disposition, in-hospital complications, and cost of RA-THA versus M-THA and CA-THA versus M-THA, as well as trends in use and uptake over a ten-year period, and future projections of uptake and use of RA-THA and CA-THA. METHODS: The National Inpatient Sample was queried for primary THAs (2008 to 2017) which were categorized into RA-THA, CA-THA, and M-THA. Past and projected use, demographic characteristics distribution, income, type of insurance, location, and healthcare setting were compared among the three cohorts. In-hospital complications, LOS, discharge disposition, and in-hospital costs were compared between propensity score-matched cohorts of M-THA versus RA-THA and M-THA versus CA-THA to adjust for baseline characteristics and comorbidities. RESULTS: RA-THA and CA-THA did not exhibit any clinically meaningful reduction in mean LOS (RA-THA 2.2 days (SD 1.4) vs 2.3 days (SD 1.8); p < 0.001, and CA-THA 2.5 days (SD 1.9) vs 2.7 days (SD 2.3); p < 0.001, respectively) compared to their respective propensity score-matched M-THA cohorts. RA-THA, but not CA-THA, had similar non-home discharge rates to M-THA (RA-THA 17.4% vs 18.5%; p = 0.205, and 18.7% vs 24.9%; p < 0.001, respectively). Implant-related mechanical complications were lower in RA-THA (RA-THA 0.5% vs M-THA 3.1%; p < 0.001, and CA-THA 1.2% vs M-THA 2.2%; p < 0.001), which was associated with a significantly lower in-hospital dislocation (RA-THA 0.1% vs M-THA 0.8%; p < 0.001). Both RA-THA and CA-THA demonstrated higher mean higher index in-hospital costs (RA-THA $18,416 (SD $8,048) vs M-THA $17,266 (SD $8,396); p < 0.001, and CA-THA $20,295 (SD $8,975) vs M-THA $18,624 (SD $9,226); p < 0.001, respectively). Projections indicate that 23.9% and 3.2% of all THAs conducted in 2025 will be robotic arm- and computer-assisted, respectively. Projections indicated that RA-THA use may overtake M-THA by 2028 (48.3%) and reach 65.8% of all THAs by 2030. CONCLUSION: Technology-assisted THA, particularly RA-THA, may provide value by lowering in-hospital early dislocation rates and and other in-hospital metrics compared to M-THA. Higher index-procedure and hospital costs warrant further comprehensive cost analyses to determine the true added value of RA-THA in the episode of care, particularly since we project that one in four THAs in 2025 and two in three THA by 2030 will use RA-THA technology. Cite this article: Bone Joint J 2021;103-B(9):1488-1496.


Assuntos
Procedimentos Cirúrgicos Robóticos , Adulto , Idoso , Idoso de 80 Anos ou mais , Artroplastia de Quadril/métodos , Bases de Dados Factuais , Feminino , Previsões , Humanos , Tempo de Internação/estatística & dados numéricos , Masculino , Pessoa de Meia-Idade , Complicações Pós-Operatórias/epidemiologia , Estudos Retrospectivos , Cirurgia Assistida por Computador , Estados Unidos/epidemiologia
7.
Recurso na Internet em Inglês | LIS - Localizador de Informação em Saúde | ID: lis-48404

RESUMO

Advice on what to do during an earthquake varies depending on the country. For example, evacuation is not recommended within the United States. According to Geohazards International, if you currently live in Haiti and are inside your house when you feel an earthquake, this is what to do: If you are inside and can easily get out, evacuate to a safe open place covering your head and your neck. Head to an open space where walls and electric poles cannot fall on you.    If you can’t evacuate, drop where you are, cover your head and neck with one arm and get under a sturdy table, and then hold on to the table legs until the shaking stops. Stay away from landslide areas and hillsides with cracks, as aftershocks can cause new landslides and existing landslides to move again.


Assuntos
Previsões/métodos , Escala Richter , Haiti , Terremotos
8.
Recurso na Internet em Inglês | LIS - Localizador de Informação em Saúde | ID: lis-48405

RESUMO

GHI’s staff is comprised of experienced professionals with diverse backgrounds, including earthquake science, engineering, medicine, law, communications, finance and international development.


Assuntos
Terremotos , Previsões , Haiti
9.
BMC Public Health ; 21(1): 1575, 2021 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-34416859

RESUMO

BACKGROUND: Salmonella infection (salmonellosis) is a common infectious disease leading to gastroenteritis, dehydration, uveitis, etc. Internet search is a new method to monitor the outbreak of infectious disease. An internet-based surveillance system using internet data is logistically advantageous and economical to show term-related diseases. In this study, we tried to determine the relationship between salmonellosis and Google Trends in the USA from January 2004 to December 2017. METHODS: We downloaded the reported salmonellosis in the USA from the National Outbreak Reporting System (NORS) from January 2004 to December 2017. Additionally, we downloaded the Google search terms related to salmonellosis from Google Trends in the same period. Cross-correlation analysis and multiple regression analysis were conducted. RESULTS: The results showed that 6 Google Trends search terms appeared earlier than reported salmonellosis, 26 Google Trends search terms coincided with salmonellosis, and 16 Google Trends search terms appeared after salmonellosis were reported. When the search terms preceded outbreaks, "foods" (t = 2.927, P = 0.004) was a predictor of salmonellosis. When the search terms coincided with outbreaks, "hotel" (t = 1.854, P = 0.066), "poor sanitation" (t = 2.895, P = 0.004), "blueberries" (t = 2.441, P = 0.016), and "hypovolemic shock" (t = 2.001, P = 0.047) were predictors of salmonellosis. When the search terms appeared after outbreaks, "ice cream" (t = 3.077, P = 0.002) was the predictor of salmonellosis. Finally, we identified the most important indicators of Google Trends search terms, including "hotel" (t = 1.854, P = 0.066), "poor sanitation" (t = 2.895, P = 0.004), "blueberries" (t = 2.441, P = 0.016), and "hypovolemic shock" (t = 2.001, P = 0.047). In the future, the increased search activities of these terms might indicate the salmonellosis. CONCLUSION: We evaluated the related Google Trends search terms with salmonellosis and identified the most important predictors of salmonellosis outbreak.


Assuntos
Gastroenterite , Infecções por Salmonella , Surtos de Doenças , Previsões , Gastroenterite/epidemiologia , Humanos , Internet , Ferramenta de Busca
10.
Sci Rep ; 11(1): 16587, 2021 08 16.
Artigo em Inglês | MEDLINE | ID: mdl-34400735

RESUMO

The rapid spread of the COVID-19 pandemic has raised huge concerns about the prospect of a major health disaster that would result in a huge number of deaths. This anxiety was largely fueled by the fact that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for the disease, was so far unknown, and therefore an accurate prediction of the number of deaths was particularly difficult. However, this prediction is of the utmost importance for public health authorities to make the most reliable decisions and establish the necessary precautions to protect people's lives. In this paper, we present an approach for predicting the number of deaths from COVID-19. This approach requires modeling the number of infected cases using a generalized logistic function and using this function for inferring the number of deaths. An estimate of the parameters of the proposed model is obtained using a Particle Swarm Optimization algorithm (PSO) that requires iteratively solving a quadratic programming problem. In addition to the total number of deaths and number of infected cases, the model enables the estimation of the infection fatality rate (IFR). Furthermore, using some mild assumptions, we derive estimates of the number of active cases. The proposed approach was empirically assessed on official data provided by the State of Qatar. The results of our computational study show a good accuracy of the predicted number of deaths.


Assuntos
Algoritmos , COVID-19/mortalidade , Previsões/métodos , SARS-CoV-2/patogenicidade , Adolescente , Adulto , Distribuição por Idade , Idoso , Idoso de 80 Anos ou mais , COVID-19/diagnóstico , COVID-19/virologia , Teste para COVID-19/estatística & dados numéricos , Criança , Pré-Escolar , Simulação por Computador , Feminino , Humanos , Lactente , Recém-Nascido , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Mortalidade/tendências , Pandemias/estatística & dados numéricos , Catar/epidemiologia , Medição de Risco/métodos , Medição de Risco/estatística & dados numéricos , SARS-CoV-2/isolamento & purificação , Adulto Jovem
11.
BMC Health Serv Res ; 21(1): 813, 2021 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-34389014

RESUMO

BACKGROUND: Artificial Intelligence (AI) innovations in radiology offer a potential solution to the increasing demand for imaging tests and the ongoing workforce crisis. Crucial to their adoption is the involvement of different professional groups, namely radiologists and radiographers, who work interdependently but whose perceptions and responses towards AI may differ. We aim to explore the knowledge, awareness and attitudes towards AI amongst professional groups in radiology, and to analyse the implications for the future adoption of these technologies into practice. METHODS: We conducted 18 semi-structured interviews with 12 radiologists and 6 radiographers from four breast units in National Health Services (NHS) organisations and one focus group with 8 radiographers from a fifth NHS breast unit, between 2018 and 2020. RESULTS: We found that radiographers and radiologists vary with respect to their awareness and knowledge around AI. Through their professional networks, conference attendance, and contacts with industry developers, radiologists receive more information and acquire more knowledge of the potential applications of AI. Radiographers instead rely more on localized personal networks for information. Our results also show that although both groups believe AI innovations offer a potential solution to workforce shortages, they differ significantly regarding the impact they believe it will have on their professional roles. Radiologists believe AI has the potential to take on more repetitive tasks and allow them to focus on more interesting and challenging work. They are less concerned that AI technology might constrain their professional role and autonomy. Radiographers showed greater concern about the potential impact that AI technology could have on their roles and skills development. They were less confident of their ability to respond positively to the potential risks and opportunities posed by AI technology. CONCLUSIONS: In summary, our findings suggest that professional responses to AI are linked to existing work roles, but are also mediated by differences in knowledge and attitudes attributable to inter-professional differences in status and identity. These findings question broad-brush assertions about the future deskilling impact of AI which neglect the need for AI innovations in healthcare to be integrated into existing work processes subject to high levels of professional autonomy.


Assuntos
Inteligência Artificial , Radiologia , Previsões , Humanos , Radiografia , Radiologistas
12.
Artigo em Inglês | MEDLINE | ID: mdl-34344766

RESUMO

OBJECTIVES: The COVID-19 pandemic has had an unprecedented impact across primary care. Primary care services have seen an upheaval, and more and more patients are engaging in telephone consultations in order to maintain social distancing. In the present study, we seek to quantify the effect of the pandemic on primary care prescribing. DESIGN: We conducted a retrospective analysis of the English Prescribing Dataset from January 2014 to November 2020, totalling 7 542 293 921 prescriptions. Data were separated into prepandemic and pandemic sets. A Holt-Winters predictive model was used to forecast individual drug prescribing based on historic trends. Observed data were compared with the forecast quantitatively and qualitatively. SETTING: All prescriptions signed in England and dispensed during the years 2014-2020. PARTICIPANTS: All residents of England who received a prescription from primary care facilities during 2014-2020. RESULTS: Prescribing of numerous health-critical medications was above predicted in March 2020, including salbutamol (53.0% (99% CI (41.2% to 66.9%))), insulin aspart (26.9% (99% CI (18.5% to 36.6%))) and tacrolimus (18.6% (99% CI (8.3% to 31.1%))). Medications for end-of-life symptom control increased in April, including levomepromazine hydrochloride (94.7% (99% CI (54.6% to 163.0%))). Medications requiring face-to-face visits decreased, including the local anaesthetic bupivacaine hydrochloride (86.6% (99% CI (89.3% to 82.0%))). There was no observed change in medications relating to type 2 diabetes, hypertension or mental health conditions. CONCLUSIONS: Significantly increased prescribing of several medications was observed, especially among those critical for health. A dramatic spike in end-of-life prescribing highlights the adversity faced by community practitioners during 2020. Medications involving face-to-face consultations declined, as did contraceptives, travel-related vaccines and drugs used in dementia and Parkinson's disease. Drugs relating to type 2 diabetes, hypertension and mental health were unchanged.


Assuntos
COVID-19/tratamento farmacológico , Prescrições de Medicamentos , Padrões de Prática Médica , Atenção Primária à Saúde , Inglaterra , Previsões , Humanos , Pandemias , Estudos Retrospectivos , SARS-CoV-2
13.
Artigo em Inglês | MEDLINE | ID: mdl-34444224

RESUMO

Attending to the ever-expanding list of factors impacting work, the workplace, and the workforce will require innovative methods and approaches for occupational safety and health (OSH) research and practice. This paper explores strategic foresight as a tool that can enhance OSH capacity to anticipate, and even shape, the future as it pertains to work. Equal parts science and art, strategic foresight includes the development and analysis of plausible alternative futures as inputs to strategic plans and actions. Here, we review several published foresight approaches and examples of work-related futures scenarios. We also present a working foresight framework tailored for OSH and offer recommendations for next steps to incorporate strategic foresight into research and practice in order to advance worker safety, health, and well-being.


Assuntos
Saúde do Trabalhador , Local de Trabalho , Previsões , Recursos Humanos
14.
BMC Med Educ ; 21(1): 453, 2021 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-34454502

RESUMO

Medical education in China has undergone significant reforms in contemporary times. As the world's largest medical education system, it is important to understand the status of China's medical education in our interdependent world. This paper highlights the current landscape of medical education in China, particularly the progress that have been made in recent years. It also examines the current topics and challenges facing China's medical educators today, and proposed recommendations for improving medical education in China. The medical education in China will produce better qualified health professionals to meet the health needs of Chinese population according to the new requirements of the "Healthy China 2030" blueprint.


Assuntos
Currículo , Educação Médica , China , Previsões , Pessoal de Saúde , Humanos
15.
Artigo em Inglês | MEDLINE | ID: mdl-34444115

RESUMO

An increasing incidence of cancer has led to high patient volumes and time challenges in ambulatory oncology clinics. By knowing how many patients are experiencing complex care needs in advance, clinic scheduling and staff allocation adjustments could be made to provide patients with longer or shorter timeslots to address symptom complexity. In this study, we used predictive analytics to forecast the percentage of patients with high symptom complexity in one clinic population in a given time period. Autoregressive integrated moving average (ARIMA) modelling was utilized with patient-reported outcome (PRO) data and patient demographic information collected over 24 weeks. Eight additional weeks of symptom complexity data were collected and compared to assess the accuracy of the forecasting model. The predicted symptom complexity levels were compared with observation data and a mean absolute predicting error of 5.9% was determined, indicating the model's satisfactory accuracy for forecasting symptom complexity levels among patients in this clinic population. By using a larger sample and additional predictors, this model could be applied to other clinics to allow for tailored scheduling and staff allocation based on symptom complexity forecasting and inform system level models of care to improve outcomes and provide higher quality patient care.


Assuntos
Instituições de Assistência Ambulatorial , Modelos Estatísticos , Previsões , Humanos , Incidência , Medidas de Resultados Relatados pelo Paciente
16.
Artigo em Inglês | MEDLINE | ID: mdl-34444184

RESUMO

BACKGROUND: Reports have indicated a negative trend in cardiorespiratory fitness (CRF) in the general population. However, trends in relation to different occupational groups are missing. Therefore, the aim of our study was to examine the trends in CRF during the last 20 years, and to provide a prognosis of future trends in CRF, in different occupational groups of Swedish workers. METHODS: Data from 516,122 health profile assessments performed between 2001 to 2020 were included. CRF was assessed as maximal oxygen consumption and was estimated from a submaximal cycling test. Analyses include CRF as a weighted average, standardized proportions with low CRF (<32 mL/min/kg), adjusted annual change in CRF, and forecasting of future trends in CRF. RESULTS: There was a decrease in CRF over the study period, with the largest decrease in both absolute and relative CRF seen for individuals working in administrative and customer service (-10.1% and -9.4%) and mechanical manufacturing (-6.5% and -7.8%) occupations. The greatest annual decrease was seen in transport occupations (-1.62 mL/min/kg, 95% CI -0.190 to -0.134). Men and younger individuals had in generally a more pronounced decrease in CRF. The proportion with a low CRF increased, with the greatest increase noted for blue-collar and low-skilled occupations (range: +19% to +27% relative change). The forecast analyses predicted a continuing downward trend of CRF. CONCLUSION: CRF has declined in most occupational groups in Sweden over the last two decades, with a more pronounced decline in blue-collar and low-skilled occupational groups.


Assuntos
Aptidão Cardiorrespiratória , Teste de Esforço , Previsões , Humanos , Masculino , Ocupações , Consumo de Oxigênio , Suécia
17.
Nat Commun ; 12(1): 4720, 2021 08 05.
Artigo em Inglês | MEDLINE | ID: mdl-34354055

RESUMO

Forecasting the evolution of contagion dynamics is still an open problem to which mechanistic models only offer a partial answer. To remain mathematically or computationally tractable, these models must rely on simplifying assumptions, thereby limiting the quantitative accuracy of their predictions and the complexity of the dynamics they can model. Here, we propose a complementary approach based on deep learning where effective local mechanisms governing a dynamic on a network are learned from time series data. Our graph neural network architecture makes very few assumptions about the dynamics, and we demonstrate its accuracy using different contagion dynamics of increasing complexity. By allowing simulations on arbitrary network structures, our approach makes it possible to explore the properties of the learned dynamics beyond the training data. Finally, we illustrate the applicability of our approach using real data of the COVID-19 outbreak in Spain. Our results demonstrate how deep learning offers a new and complementary perspective to build effective models of contagion dynamics on networks.


Assuntos
COVID-19/epidemiologia , Controle de Doenças Transmissíveis/métodos , Aprendizado Profundo , Surtos de Doenças/prevenção & controle , Previsões/métodos , Humanos , Modelos Teóricos , SARS-CoV-2 , Espanha/epidemiologia
19.
Compend Contin Educ Dent ; 42(6): e1-e4, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34412481

RESUMO

2021 is shaping up to be the year of artificial intelligence (AI) for the dental industry. Not only are providers adopting AI at a rapid pace, payers are tapping this technology to automate their claims review operations and reduce friction in provider interactions. In part three of this six-part dental AI series, the authors offer their view from the frontlines of dental claims processing and the promising future impact of AI. Representing clinical and business viewpoints, the authors draw on experience working at and with some of the largest dental payers in the country. This article presents a forward-looking perspective on the potential of dental AI to improve payer-provider relations, streamline claims review, and ultimately provide an improved patient experience.


Assuntos
Inteligência Artificial , Previsões , Humanos
20.
BMC Res Notes ; 14(1): 319, 2021 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-34419141

RESUMO

OBJECTIVE: Reported rainfall data from multiple rain gauges and its corresponding estimate from Dual-Polarization (Dual-Pol) radar is presented here. The ordered set of data pairs were collected from multiple peer reviewed publications spanning across the last decade. DATA DESCRIPTION: Taken from multiple sources, the data set represents several radar sites and rain gauge sites combined for 12,734 data points. The data is relevant in various applications of hydrometeorology and engineering as well as weather forecasting. Further, the importance of accuracy in radar precipitation estimates continues to increase, necessitating the incorporation of as much data as possible.


Assuntos
Radar , Chuva , Previsões
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