Prescriptions

An AI-Assisted Adaptive Boolean Rubric for exercise prescription evaluation: A pilot validation study.

BACKGROUND: The quality assessment of personalized exercise prescriptions is currently hampered by the subjectivity and inefficiency of traditional rating scales. Artificial intelligence (AI) presents a transformative opportunity for objective, scalable evaluation. OBJECTIVES: This pilot study aimed to develop an AI-assisted evaluation framework and assess the feasibility, reliability, and efficie...

Reveal a risk and potential mechanism for keratoconus progression with isotretinoin: Toxicogenomic, transcriptomics and real-world evidence insights.

PURPOSE: Limited clinical data and unstable animal models hinder understanding isotretinoin-induced keratoconus. We addressed this by integrating pharmacovigilance with computational approaches. METHODS: Isotretinoin-associated ocular surface adverse events were extracted from the FDA Adverse Event Reporting System (FAERS). Disproportionality analyses detected pharmacovigilance signals, and age co...

MDM-DTA: Message Passing Neural Network with molecular descriptors and Mixture of Experts for drug-target affinity prediction.

BACKGROUND AND OBJECTIVE: Drug-target affinity (DTA) prediction is a pivotal task in computational drug discovery, enabling the estimation of binding ...

Review on electrochemical sensors for anticancer drug susceptibility testing.

Anticancer drug susceptibility tests play an essential role in areas such as drug development, pharmacokinetic research, and precision oncology. Acros...

Drug Repurposing in Oncology: A Strategic Pathway to Unlocking New Therapeutic Potential.

The growing number of cancer cases and deaths highlights the urgent need for innovative treatment approaches. One technique that has lately been recog...

From passive prevention to proactive intervention: An AI-assisted integrated governance system for algal bloom monitoring and control.

Algal blooms, characterized by the excessive proliferation of microalgae in a freshwater or marine ecosystem, have evolved into a global ecological, h...

An Interpretable Machine Learning Model Based on MRI Features for Predicting Pain Severity in Temporomandibular Disorders.

BACKGROUND: Chronic pain around the temporomandibular joint (TMJ) and masticatory muscles is a primary symptom of temporomandibular disorders (TMD). H...

Utility and limitations of the FDA adverse events reporting system public dashboard for safety analyses: a case study with vesicular monoamine transporter 2 inhibitors.

INTRODUCTION: The United States Food and Drug Administration (FDA) requires post-marketing surveillance of approved drugs, and pharmaceutical manufact...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Observation and Localization in CT Images.

Pancreatic cancer remains one of the deadliest malignancies, primarily because of its subtle CT appearance and frequent late-stage diagnosis. We intro...

Developing a novel framework using optimized active stacking and explainable AI for heart disease prediction.

BACKGROUND AND OBJECTIVE: Heart disease is still the top driver of death worldwide, and developing accurate, interpretable, and efficient predictive s...

Evaluating the Performance of Claude 3.7 Sonnet in Data Extraction Automation for Systematic Literature Reviews.

OBJECTIVES: To evaluate the performance of Claude 3.7 Sonnet in automating data extraction for systematic literature reviews (SLRs). METHODS: An artif...

Curvature-aware selective feature interaction network for skin lesion segmentation.

With the increasing prevalence of dermatological diseases, skin lesion segmentation has gained significant attention in medical image analysis. Despit...

Risk prediction models for adverse drug reactions in pediatrics: a scoping review.

INTRODUCTION: Predictive models play a critical role in enhancing medication safety in clinical practice. While multiple models for adverse drug react...

Design and optimization of indomethacin-loaded solid dispersion orally dissolving films: Machine learning and molecular dynamics study.

Indomethacin (IND) is a nonsteroidal anti-inflammatory drug (NSAID) with anti-inflammatory, analgesic, and antipyretic properties, and is widely used ...

Effects of Real-Time Notification of AI-Detected Incidental Coronary Artery Calcium on Statin Prescription: The NOTIFY-PICTURE Trial.

Deep learning framework for bronchoscopic diagnosis of burn inhalation injury.

Burn inhalation injury (BII) increases mortality and morbidity in burns patients. Accurate bronchoscopic grading, as the gold standard diagnostic moda...

Large language models accurately extract aortic information from abdominal imaging reports in a large, real-world database.

OBJECTIVE: Maintaining robust surveillance programs for abdominal aortic aneurysms (AAAs) is important, but these programs are expensive and labor-int...

Medication-based mortality prediction in COPD using machine learning and conventional statistical methods.

BACKGROUND: Predicting mortality in chronic obstructive pulmonary disease (COPD) patients supports clinical decision-making and resource allocation. W...

Transcription Accuracy of Automatic Speech Recognition for Orthodontic Clinical Records.

Accurate clinical records are fundamental to dental practice. Automatic speech recognition (ASR) has the capacity to convert spoken clinical language ...

Artificial intelligence to automatically identify reverse shoulder arthroplasty implant brands on postoperative radiographs including uncertainty quantification.

BACKGROUND: Identifying the brand of reverse shoulder arthroplasty (rTSA) implanted is key in the postoperative evaluation of patients, a process that...