Latest AI and machine learning research in prescriptions for healthcare professionals.
BACKGROUND AND OBJECTIVE: The fluorescence resonance energy transfer (FRET) two-hybrid assay enables quantification of the stoichiometry and binding affinity of protein interactions directly in living cells, but its broader application remains constrained by labor-intensive manual image analysis and high computational complexity. This study leverages deep learning to accurately extract FRET two-hy...
Creatine (CR) and Caffeine (CAF) are popular and extensively consumed dietary supplements (DS) on a global scale. Although the concomitant use of these substances may augment their effectiveness, it results in the risk of adulteration through mislabeling or the undisclosed addition of CAF. The use of reliable and rapid analytical screening tools is essential to ensure product integrity and protect...
BACKGROUND AND OBJECTIVES: Use of companion robot pets to reduce social isolation and loneliness in older people is well-established. Outcomes associa...
OBJECTIVES: To evaluate the effect of image type on the performance of a deep learning classification model for decision-making in orthodontic treatme...
Colloidal drug aggregates are amorphous nanoparticles formed by the self-assembly of hydrophobic small molecule drugs. They can be leveraged as drug-r...
BACKGROUND: Cervical spine (c-spine) injuries can lead to significant disability and mortality. Although stabilization is the primary management for s...
OBJECTIVE: The purpose of this study was to develop a lightweight multimodal deep learning model for accurately predicting the risk of postoperative v...
BACKGROUND: While medication for opioid use disorder (MOUD) is effective for a significant proportion of patients, many return to using opioids during...
The treatment of depression involves numerous barriers, both before and after individuals seek professional care. Online health communities (OHCs) hav...
OBJECTIVES: Electromyography (EMG) is increasingly applied in oncology to monitor neuromuscular impairment, treatment toxicities, and rehabilitation o...
This narrative, perspective-style review proposes a structured framework for how artificial intelligence (AI) may reshape key steps of the echocardiog...
Predicting adverse drug events (ADEs) in outpatient settings is crucial for improving medication safety, identifying high-risk patients and reducing h...
Magnetically guided drug delivery (MGDD) employs magnetic forces acting on magnetically responsive drug delivery systems (DDS) to direct therapeutic a...
BACKGROUND: Curative-intent radiotherapy (RT) or chemoradiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC) frequently leads to mucosit...
INTRODUCTION: Self-care and self-medication are increasingly viewed as helpful approaches to managing minor ailments; however, patients are often not ...
Accurately quantifying protein-DNA interactions (PDIs) is critical for understanding biological processes and facilitating drug design. However, the i...
Traditional knowledge from medicinal plants receives substantial analysis through the field of ethnopharmacology in its role for drug discovery. AI te...
OBJECTIVE: To develop a statistical model to capture medication dosing for proton pump inhibitors (PPIs) using structured data from electronic health ...
BACKGROUND: Accurate plane positioning is important for high-quality cardiac MRI images but requires specialized training, limiting accessibility. PUR...
BackgroundAn artificial intelligence (AI)-enabled rule-out device may autonomously remove patient images unlikely to have cancer from radiologist revi...