Identifying intentional injuries among children and adolescents based on Machine Learning.
Yin Xiling et al. PloS one 2021 16(1) e0245437

Machine Learning Improves Early Prediction of Small-for-Gestational-Age Births and Reveals Nuchal Fold Thickness as Unexpected Predictor.
Nee Saw Shier et al. Prenatal diagnosis 2021 Jan

Improving screening systems of autism by machine learning with data sampling.
Scott Alexander James Walter et al. Technology and health care : official journal of the European Society for Engineering and Medicine 2021 Jan

Deconstructing Racial and Ethnic Disparities in Breast Cancer
JA Sparano et al, JAMA Oncology, January 21,2021

Lung cancer survival period prediction and understanding: Deep learning approaches.
Doppalapudi Shreyesh et al. International journal of medical informatics 2020 Dec 148104371

WeGleNet: A weakly-supervised convolutional neural network for the semantic segmentation of Gleason grades in prostate histology images.
Silva-Rodríguez Julio et al. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society 2021 Jan 88101846

Development and Cost Analysis of a Lung Nodule Management Strategy Combining Artificial Intelligence and Lung Reporting and Data Systems for Baseline Lung Cancer Screening.
Adams Scott J et al. Journal of the American College of Radiology : JACR 2021 Jan

Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study.
Fanizzi Annarita et al. Cancers 2021 Jan 13(2)

Machine learning applications in radiation oncology: Current use and needs to support clinical implementation.
Brouwer Charlotte L et al. Physics and imaging in radiation oncology 2020 Oct 16144-148

Early Detection of Prediabetes and T2DM Using Wearable Sensors and Internet-of-Things-Based Monitoring Applications
MM Baig et al, Appl Clin Informatics, January 2021

Automated detection of patients with dementia whose symptoms have been identified in primary care but have no formal diagnosis: a retrospective case-control study using electronic primary care records.
Ford Elizabeth et al. BMJ open 2021 Jan 11(1) e039248

Use of Machine Learning to Determine the Information Value of a BMI Screening Program.
Zare Samane et al. American journal of preventive medicine 2021 Jan

Predictive modeling of depression and anxiety using electronic health records and a novel machine learning approach with artificial intelligence.
Nemesure Matthew D et al. Scientific reports 2021 Jan 11(1) 1980

The SEE Study: Safety, Efficacy, and Equity of Implementing Autonomous Artificial Intelligence for Diagnosing Diabetic Retinopathy in Youth.
Wolf Risa M et al. Diabetes care 2021 Jan

Using electronic health records and claims data to identify high-risk patients likely to benefit from palliative care.
Guo Aixia et al. The American journal of managed care 2021 27(1) e7-e15

Clinical value of machine learning-based interpretation of I-123 FP-CIT scans to detect Parkinson's disease: a two-center study.
Dotinga M et al. Annals of nuclear medicine 2021 Jan

Recalibrating the Use of Race in Medical Research
JP Ioannidis et al, JAMA, January 25, 2021

Recommendations for the safe, effective use of adaptive CDS in the US healthcare system: an AMIA position paper
C Petersen et al, JAMIA, January 2021

How Do Machines Learn? Artificial Intelligence as a New Era in Medicine
O Koteluk et al, J Pers Med, January 2021

Identification of Suicide Attempt Risk Factors in a National US Survey Using Machine Learning.
García de la Garza Ángel et al. JAMA psychiatry 2021 Jan

The Future of Dentistry: How AI is Transforming Dental Practices.
Balaban Christopher et al. Compendium of continuing education in dentistry (Jamesburg, N.J. : 1995) 2021 Jan 42(1) 14-17

Stress testing reveals gaps in clinic readiness of image-based diagnostic artificial intelligence models.
Young Albert T et al. NPJ digital medicine 2021 Jan 4(1) 10

Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.
Muehlematter Urs J et al. The Lancet. Digital health 2021 Jan

Emerging Applications of Machine Learning in Food Safety.
Deng Xiangyu et al. Annual review of food science and technology 2021 Jan

Using natural language processing to classify social work interventions.
Bako Abdulaziz Tijjani et al. The American journal of managed care 2021 27(1) e24-e31

From Code to Bedside: Implementing Artificial Intelligence Using Quality Improvement Methods.
Smith Margaret et al. Journal of general internal medicine 2021 Jan

Deep learning interpretation of echocardiograms.
Ghorbani Amirata et al. NPJ digital medicine 2020 Jan 3(1) 10

Assessing the Role of Pericardial Fat as a Biomarker Connected to Coronary Calcification-A Deep Learning Based Approach Using Fully Automated Body Composition Analysis.
Kroll Lennard et al. Journal of clinical medicine 2021 Jan 10(2)

Risk factors associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention: a 10-year follow-up comparing random survival forest and Cox proportional-hazards model.
Farhadian Maryam et al. BMC cardiovascular disorders 2021 Jan 21(1) 38

Deep Learning applications for COVID-19.
Shorten Connor et al. Journal of big data 2021 8(1) 18

Deep Learning Models for Predicting Severe Progression in COVID-19-infected Patients.
Ho Thao Thi et al. JMIR medical informatics 2021 Jan

The risk of racial bias while tracking influenza-related content on social media using machine learning.
Lwowski Brandon et al. Journal of the American Medical Informatics Association : JAMIA 2021 Jan

How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future.
Malik Yashpal Singh et al. Reviews in medical virology 2020 Dec e2205

Machine learning prediction of neurocognitive impairment among people with HIV using clinical and multimodal magnetic resonance imaging data.
Xu Yunan et al. Journal of neurovirology 2021 Jan

Predicting Progression to Septic Shock in the Emergency Department Using an Externally Generalizable Machine-Learning Algorithm.
Wardi Gabriel et al. Annals of emergency medicine 2021 Jan

Machine-learning algorithm incorporating capacitated sperm intracellular pH predicts conventional in vitro fertilization success in normospermic patients.
Gunderson Stephanie Jean et al. Fertility and sterility 2021 Jan