AIMC Topic: Artificial Intelligence

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AI-driven discovery of novel extracellular matrix biomarkers in pelvic organ prolapse.

PLoS computational biology
Deep learning for protein function prediction faces significant challenges in identifying disease-specific proteins. We present Extracellular Matrix Protein Predictor (EPOP), an advanced transfer learning framework leveraging protein language models ...

Artificial intelligence for the prediction of posthepatectomy recurrence in hepatocellular carcinoma: a systematic review and meta-analysis.

Annals of medicine
OBJECTIVE: Posthepatectomy recurrence of hepatocellular carcinoma (HCC) is a major cause of poor prognosis. Accurate prediction is essential for reducing the burden of advanced disease and improving outcomes.

AI-driven prognostics in pediatric bone marrow transplantation: a CAD approach with Bayesian and PSO optimization.

BMC medical informatics and decision making
Bone marrow transplantation (BMT) is a critical treatment for various hematological diseases in children, offering a potential cure and significantly improving patient outcomes. However, the complexity of matching donors and recipients and predicting...

"I can no longer give take-home exams": Health professionals educators' experiences and perceptions regarding the use of artificial intelligence in health professions education in Uganda.

BMC medical education
INTRODUCTION: Artificial intelligence (AI) tools offer immense opportunities and challenges for medical education. However, there is limited information about the use of AI among health professional educators, particularly in low- and middle-income c...

AI-driven chemotoxicity prediction in colorectal cancer: impact of race, SDOH, and biological aging.

BMC cancer
BACKGROUND: Patients with colorectal cancer (CRC) often experience chemotoxicity that impacts treatment adherence, survival, and quality of life. Early screening for chemotoxicity risk is vital, yet comprehensive predictive models are lacking. The ob...

LLM ethics benchmark: a three-dimensional assessment system for evaluating moral reasoning in large language models.

Scientific reports
This study establishes a novel framework for systematically evaluating the moral reasoning capabilities of large language models (LLMs) as they increasingly integrate into critical societal domains. Current assessment methodologies lack the precision...

Study protocol for an open-label, single-arm, mixed methods feasibility study of the MWIQ AI-powered decision support tool for diabetes management in GP practices.

BMJ open
INTRODUCTION: Diabetes affects ~10% of the world's population and is rising. Treatment costs in the UK are ~15% of the NHS budget. Diabetes-related complications can be lowered through better evidence-based clinician management and patient self-manag...

A Trust-Aware Architecture for Personalized Digital Health: Integrating Blueprint Personas and Ontology-Based Reasoning.

Journal of medical systems
This paper presents a trust-aware architecture for personalized digital health that combines user modeling, symbolic reasoning, and adaptive trust mechanisms. The proposed system uses Blueprint Personas to capture detailed patient profiles, including...

Clinician perspectives on explainability in AI-driven closed-loop neurotechnology.

Scientific reports
Artificial Intelligence (AI) holds promise for advancing the field of neurotechnology and accelerating its clinical translation. AI-driven clinical neurotechnologies leverage the power of non-linear algorithms to analyze complex brain data and enable...

Opportunities and Challenges of Using Artificial Intelligence in Predicting Clinical Outcomes and Length of Stay in Neonatal Intensive Care Units: Systematic Review.

Journal of medical Internet research
BACKGROUND: The use of artificial intelligence (AI) in health care has been steadily increasing for over 2 decades. Integrating AI into neonatal intensive care units (NICUs) has promise as it has the potential to reshape neonatal care and improve out...