Latest AI and machine learning research in clinical trials for healthcare professionals.
The absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of drugs are critical to their efficacy and safety in clinical trials; however, traditional machine learning methods have limited generalization ability in ADMET prediction due to insufficient data. To address this issue, we developed DCPM-ADMET, an innovative pre-trained model with higher accuracy, whose architec...
Many cancer monotherapies demonstrate limited clinical efficacy, making combination therapies a relevant treatment strategy. The extensive number of potential drug combinations and context-specific response profiles complicates the prediction of drug combination responses. Existing computational models are typically trained to predict a single aggregated synergy score, which summarises drug respon...
OBJECTIVES: To investigate the views and experiences of principal investigators (PIs) based in sub-Saharan Africa (SSA) regarding publication bias of ...
INTRODUCTION: The integration of artificial intelligence (AI) into addiction research has expanded rapidly, yet it remains unclear how psychosocial, b...
BACKGROUND: Digital surgery technologies, including robotic systems, artificial intelligence (AI) algorithms, augmented reality platforms, and advance...
BACKGROUND: To determine the levels of attitudes toward artificial intelligence(AI), creative self-efficacy, and problem-solving ability among nursing...
UNLABELLED: The Gulf of Mexico/Gulf of America provides ecosystem services derived from marine biodiversity and oil and gas resources. Threats posed b...
PURPOSE OF REVIEW: This review explores the rapidly evolving integration of Generative Artificial Intelligence (GenAI) in mental health care. It aims ...
Traumatic brain injury (TBI) is a leading cause of persistent cognitive, motor, and neuropsychiatric impairment, arising from both the initial mechani...
BACKGROUND: Artificial intelligence has gained relevance due to its potential to reduce the workload in evidence synthesis or bibliometric projects. W...
INTRODUCTION: The global prevalence of heart failure continues to increase, particularly in ageing populations. Many older patients receiving home-bas...
OBJECTIVES: To evaluate the feasibility of using wearable inertial measurement units (IMUs; small body-worn sensors that capture linear acceleration a...
Reirradiation (reRT) has become an essential therapeutic option for selected patients with locoregional recurrences, when surgery or systemic therapie...
Early identification of children at risk for persistent asthma is challenging because preschool respiratory symptoms are heterogeneous and often overl...
Cognitive decline with age and other clinical conditions are linked with reduced hypothalamic-pituitary-adrenal (HPA) axis function. Stimulating the H...
Cancers of unknown primary (CUP) refer to a highly heterogeneous group of metastatic tumors whose primary site remains undetectable despite comprehens...
OBJECTIVES: To assess the economic impact of Artificial Intelligence (AI)-assisted stress echocardiography (SE) in the National Health Service (NHS) d...
BACKGROUND: Developing high-quality multiple-choice examinations in medical education is time- and resource-intensive. Large language models (LLMs) of...
OBJECTIVE: To identify factors associated with the achievement of independent gait after the robot-assisted gait training (RAGT) with an exoskeletal w...
BACKGROUND: Family caregivers experience conflicts in caring for people with Alzheimer's dementia (PWD; e.g., siblings disagreeing, advocating with pr...