AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models.

BMC musculoskeletal disorders
BACKGROUND: Identifying determinants of low bone mineral density (BMD) is crucial for understanding the underlying pathobiology and developing effective prevention and management strategies. Here we applied machine learning (ML) algorithms to predict...

How AI sources can increase openness to opposing views.

Scientific reports
Exposure to counterattitudinal information has been shown to yield mixed effects on attitude polarization. The current research explores the differential impact of such information when generated by artificial intelligence (AI) versus human sources. ...

Artificial intelligence-guided distal radius fracture detection on plain radiographs in comparison with human raters.

Journal of orthopaedic surgery and research
BACKGROUND: The aim of this study was to compare the performance of artificial intelligence (AI) in detecting distal radius fractures (DRFs) on plain radiographs with the performance of human raters.

Deep learning health space model for ordered responses.

BMC medical informatics and decision making
BACKGROUND: As personalized medicine becomes more prevalent, the objective measurement and visualization of an individual's health status are becoming increasingly crucial. However, as the dimensions of data collected from each individual increase, t...

Artificial intelligence generated 3D body composition predicts dose modifications in patients undergoing neoadjuvant chemotherapy for rectal cancer.

Journal of cancer research and clinical oncology
PURPOSE: Chemotherapy administration is a balancing act between giving enough to achieve the desired tumour response while limiting adverse effects. Chemotherapy dosing is based on body surface area (BSA). Emerging evidence suggests body composition ...

Predicting Placebo Responses Using EEG and Deep Convolutional Neural Networks: Correlations with Clinical Data Across Three Independent Datasets.

Neuroinformatics
Identifying likely placebo responders can help design more efficient clinical trials by stratifying participants, reducing sample size requirements, and enhancing the detection of true drug effects. In response to this need, we developed a deep convo...

Research on driving factors of consumer purchase intention of artificial intelligence creative products based on user behavior.

Scientific reports
With the continuous advancement of artificial intelligence (AI) technology, AIGC (AI-generated content) has increasingly permeated various sectors, leading to a significant transformation in the design industry. This study aims to explore user purcha...

Personalized prediction of negative affect in individuals with serious mental illness followed using long-term multimodal mobile phenotyping.

Translational psychiatry
Heightened negative affect is a core feature of serious mental illness. Over 90% of American adults own a smartphone, equipped with an array of sensors which can continuously and unobtrusively measure behaviors (e.g., activity levels, location, and p...

AI assistance improves people's ability to distinguish correct from incorrect eyewitness lineup identifications.

Proceedings of the National Academy of Sciences of the United States of America
Mistaken eyewitness identification is one of the leading causes of false convictions. Improving law enforcement's ability to identify correct identifications could have profound implications for criminal justice. Across two experiments, we show that ...

Developing a machine learning algorithm to predict psychotropic drugs-induced weight gain and the effectiveness of anti-obesity drugs in patients with severe mental illness: Protocol for a prospective cohort study.

PloS one
Obesity is a global public health concern, often co-occurring in patients with severe mental illnesses. The impact of psychotropic drugs-induced weight gain is augmenting the disease burden and healthcare expenditure. However, predictors of psychotro...