An overview of GeoAI applications in health and healthcare.

The moulding together of artificial intelligence (AI) and the geographic/geographic information systems (GIS) dimension creates GeoAI. There is an emerging role for GeoAI in health and healthcare, as location is an integral part of both population and individual health. This article provides an overview of GeoAI technologies (methods, tools and software), and their current and potential applications in several disciplines within public health, precision medicine, and Internet of Things-powered smart healthy cities. The potential challenges currently facing GeoAI research and applications in health and healthcare are also briefly discussed.

Digital Is Political: Why We Need a Feminist Conceptual Lens on Determinants of Digital Health.

Digital health is a rapidly emerging field that offers several promising potentials: health care delivery remotely, in urban and rural areas, in any time zone, and in times of pandemics and ecological crises. Digital health encompasses electronic health, computing science, big data, artificial intelligence, and the Internet of Things, to name but a few technical components. Digital health is part of a vision for systems medicine. The advances in digital health have been, however, uneven and highly variable across communities, countries, medical specialties, and societal contexts. This article critically examines the determinants of digital health (DDH). DDH describes and critically responds to inequities and differences in digital health theory and practice across people, places, spaces, and time. DDH is not limited to studying variability in design and access to digital technologies. DDH is situated within a larger context of the political determinants of health. Hence, this article presents an analysis of DDH, as seen through political science, and the feminist studies of technology and society. A feminist lens would strengthen systems-driven, historically and critically informed governance for DDH. This would be a timely antidote against unchecked destructive/extractive governance narratives (e.g., technocracy and patriarchy) that produce and reproduce the health inequities. Moreover, feminist framing of DDH can help cultivate epistemic competence to detect and reject false equivalences in how we understand the emerging digital world(s). False equivalence, very common in the current pandemic and post-truth era, is a type of flawed reasoning in decision-making where equal weight is given to arguments with concrete material evidence, and those that are conjecture, untrue, or unjust. A feminist conceptual lens on DDH would help remedy what I refer to in this article as "the normative deficits" in science and technology policy that became endemic with the rise of neoliberal governance since the 1980s in particular. In this context, it is helpful to recall the feminist writer Ursula K. Le Guin. Le Guin posed "what if?" questions, to break free from oppressive narratives such as patriarchy and re-imagine technology futures. It is time to envision an emancipated, equitable, and more democratic world by asking "what if we lived in a feminist world?" That would be truly awesome, for everyone, women and men, children, youth, and future generations, to steer digital technologies and the new field of DDH toward broadly relevant, ethical, experiential, democratic, and socially responsive health outcomes.

Artificial intelligence: opportunities and implications for the health workforce.

Healthcare involves cyclic data processing to derive meaningful, actionable decisions. Rapid increases in clinical data have added to the occupational stress of healthcare workers, affecting their ability to provide quality and effective services. Health systems have to radically rethink strategies to ensure that staff are satisfied and actively supported in their jobs. Artificial intelligence (AI) has the potential to augment provider performance. This article reviews the available literature to identify AI opportunities that can potentially transform the role of healthcare providers. To leverage AI's full potential, policymakers, industry, healthcare providers and patients have to address a new set of challenges. Optimizing the benefits of AI will require a balanced approach that enhances accountability and transparency while facilitating innovation.

Artificial intelligence and machine learning in orthopedic surgery: a systematic review protocol.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are interwoven into our everyday lives and have grown enormously in some major fields in medicine including cardiology and radiology. While these specialties have quickly embraced AI and ML, orthopedic surgery has been slower to do so. Fortunately, there has been a recent surge in new research emphasizing the need for a systematic review. The primary objective of this systematic review will be to provide an update on the advances of AI and ML in the field of orthopedic surgery. The secondary objectives will be to evaluate the applications of AI and ML in providing a clinical diagnosis and predicting post-operative outcomes and complications in orthopedic surgery. METHODS: A systematic search will be conducted in PubMed, ScienceDirect, and Google Scholar databases for articles written in English, Italian, French, Spanish, and Portuguese language articles published up to September 2020. References will be screened and assessed for eligibility by at least two independent reviewers as per PRISMA guidelines. Studies must apply to orthopedic interventions and acute and chronic orthopedic musculoskeletal injuries to be considered eligible. Studies will be excluded if they are animal studies and do not relate to orthopedic interventions or if no clinical data were produced. Gold standard processes and practices to obtain a clinical diagnosis and predict post-operative outcomes shall be compared with and without the use of ML algorithms. Any case reports and other primary studies assessing the prediction rate of post-operative outcomes or the ability to identify a diagnosis in orthopedic surgery will be included. Systematic reviews or literature reviews will be examined to identify further studies for inclusion, and the results of meta-analyses will not be included in the analysis. DISCUSSION: Our findings will evaluate the advances of AI and ML in the field of orthopedic surgery. We expect to find a large quantity of uncontrolled studies and a smaller subset of articles describing actual applications and outcomes for clinical care. Cohort studies and large randomized control trial will likely be needed. TRIAL REGISTRATION: The protocol will be registered on PROSPERO international prospective register of systematic reviews prior to commencement.

Technology Use for Adolescent Health and Wellness.

As avid users of technology, adolescents are a key demographic to engage when designing and developing technology applications for health. There are multiple opportunities for improving adolescent health, from promoting preventive behaviors to providing guidance for adolescents with chronic illness in supporting treatment adherence and transition to adult health care systems. This article will provide a brief overview of current technologies and then highlight new technologies being used specifically for adolescent health, such as artificial intelligence, virtual and augmented reality, and machine learning. Because there is paucity of evidence in this field, we will make recommendations for future research.

Of Slide Rules and Stethoscopes: AI and the Future of Doctoring.

Historically, the practice of medicine has been a physically intimate endeavor. Physicians have used their hands to palpate and reveal the secrets hidden within the body. Smelling the breath for the ketosis of diabetes or tasting the skin for the saltiness of cystic fibrosis were among the physician's essential practices. Today, perhaps the most defining characteristic of a brilliant clinician is the ability to synthesize many images-from electrocardiograms, ultrasounds, CT scans, and so forth-into a coherent picture that can guide our diagnosis and treatment. Yet this is rapidly becoming a Sisyphean task. Just as we are about to drown in a deluge of data, AI is throwing us a life preserver, to save not only our patients but ourselves. But where will AI take us?

Future of Radiotherapy in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as associated Epstein-Barr virus infection and high radiosensitivity. Radiotherapy has long been recognized as the mainstay for the treatment of NPC. However, the further efficacy brought by radical radiotherapy has reached the bottleneck in advanced patients, who are prone to develop recurrence and distant metastasis after treatment. The application of photon therapy makes it possible for radiation dose escalation in refractory cases and may provide second chance for recurrent patients with less unrecoverable tissue damage. The concept of adaptive radiotherapy is put forward in consideration of target volume shrinkage during treatment. The replanning procedure offers better protection for the organ at risk. However, the best timing and candidates for adaptive radiotherapy is still under debate. The current tendency of artificial intelligence in NPC mainly focuses on image recognition, auto-segmentation and dose prediction. Although artificial intelligence is still in developmental stage, the future of it is promising.To further improve the efficacy of NPC, multimodality treatment is encouraged. In-depth studies on genetic and epigenetic variations help to explain the great heterogeneity among patients, and could further be applied to precise screening and prediction, personalized radiotherapy and the evolution of targeted drugs. Given the clinical benefit of immunotherapy in other cancers, the application of immunotherapy, especially immune checkpoint inhibitor, in NPC is also of great potential. Results from ongoing clinical trials combining immunotherapy with radiotherapy in NPC are expected.