Latest AI and machine learning research in preventive care for healthcare professionals.
Diabetic retinopathy (DR) is a leading cause of vision impairment globally, necessitating early and accurate detection through effective screening methods. We focus on the integration of artificial intelligence (AI) techniques in automating and enhancing DR diagnosis. Timely detection and classification of DR severity are critical for patient management and intervention. AI-driven DR classificatio...
BACKGROUND: Drug screening constitutes the predominant paradigm for novel drug discovery. With the development of omics, drug screening has gradually developed into pharmacotranscriptomics-based drug screening (PTDS), which is different from target-based and phenotype-based drug screening. PTDS is a rapidly evolving interdisciplinary field that concurrently demands overcoming large-scale pharmacot...
PURPOSE: Diabetic retinopathy (DR) is a leading cause of vision loss in middle-aged adults globally. Although artificial intelligence (AI)-based scree...
ObjectiveTo study the implications of implementing artificial intelligence (AI) as a decision support tool in the Norwegian breast cancer screening pr...
Accurate polyp size estimation during colonoscopy is crucial for clinical decision making, follow-up, and implementation of cost-saving strategies. Ob...
This study proposed a new quality control indicator for colonoscopy, the cumulative colorectal mucosal exposure area (CCMEA), to assess mucosal exposu...
BACKGROUND: Despite KDIGO (Kidney Disease: Improving Global Outcomes) recommendations for renin-angiotensin-aldosterone system inhibitors (RAASi's) an...
Barrett esophagus (BE) is the only known histological precursor to esophageal adenocarcinoma (EAC). The incidence of EAC has risen significantly over ...
B-cell acute lymphoblastic leukemia (B-ALL) is an aggressive hematological malignancy that primarily affects children but can also occur in adults, pr...
BACKGROUND & AIMS: Endoscopic scoring of Crohn's disease (CD) is challenging, as mucosal disease is patchy with highly variable morphology, size, and ...
This study investigated radiologists' perceptions of AI-generated, patient-friendly radiology reports across three modalities: MRI, CT, and mammogram/...
Dual inhibitors of 5HT1A and 5HT7 serotonin receptors provide improved therapeutic effectiveness for depression, anxiety disorders, and neuropsychiatr...
Water exchange and artificial intelligence-based computer-aided detection (CADe) separately improve the adenoma detection rate (ADR) and number of ade...
Colorectal cancer remains a major health burden, and its early detection is crucial for effective treatment. This study investigates the use of a hand...
Cancer vaccines stimulate antitumor immunity by delivering tumor antigens and, in recent years, have emerged as a promising therapeutic strategy again...
INTRODUCTION: Strategic investment in new interventions is crucial for controlling and eliminating NTDs. However, selecting the optimal intervention c...
Neuroblastoma is an aggressive childhood cancer characterised by high relapse rates and heterogenicity. Current medical diagnostic methods involve an ...
Late detection of periodontitis has significant health implications. Screening via oral images may serve as an accessible nonclinical method. This stu...
An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms rem...
. Artificial intelligence (AI) tools for evaluating low-dose CT (LDCT) lung cancer screening examinations are used predominantly for assisting radiolo...