Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 64,191 to 64,200 of 231,309 articles

Onco-Seg: Adapting Promptable Concept Segmentation for Multi-Modal Medical Imaging

medRxiv
Medical image segmentation remains a critical bottleneck in clinical workflows, from diagnostic radiology to radiation oncology treatment planning. We present Onco-Seg, a medical imaging adaptation of Metas Segment Anything Model 3 (SAM3) that levera... read more 

Suicide- and crisis-risk detection using large language models in mental-health chatbots

medRxiv
ObjectiveLarge language models (LLMs) are increasingly embedded in mental-health chatbots, yet safe deployment is limited by two unresolved challenges: (1) suicide- and crisis-risk detection lacks a definitive ground truth and is characterized by sub... read more 

A Theoretical Framework for Quantifying Tumour Resistance to Standardized Treatments: A Novel Rudimentary Scalar Mathematical Model with Implications for Breast Cancer Prognosis and Treatment.

medRxiv
BackgroundPrecision oncology relies heavily on genomic profiling and artificial intelligence to predict therapeutic response in breast cancer. However, in low-to-middle-income countries (LMICs), these expensive modalities are inaccessible; forcing cl... read more 

Deep learning enables diagnosis of atrial cardiomyopathy from routine 12-lead electrocardiogram

medRxiv
BackgroundAtrial cardiomyopathy (AtCM) is both a cause and a consequence of atrial fibrillation and flutter (AF) and can lead to ischemic stroke. Imaging derived left atrial (LA) structure and function are used to diagnose AtCM. Considering the tight... read more 

Predicting intervertebral disc degeneration using Pyradiomics features and XGBoost classification

medRxiv
BackgroundDisc degeneration is the primary cause of low back pain, although the disc itself is not usually the source of the pain. Instead, it can lead to various clinically significant conditions that cause pain. However, there are no objective meas... read more 

Predicting Continuous Cognitive Decline: The Generalizability of a Multimodal Machine Learning Approach Including Structural MRI and Non-Brain Data

medRxiv
Aging is often accompanied by cognitive decline, but the extent, timing, and severity of this process is subject to large inter-individual variability. Predicting cognitive decline along a continuum, encompassing healthy age-related decline, mild cog... read more 

Mass spectrometry and machine learning for classification and molecular phenotyping of renal cell carcinoma and benign tumors

medRxiv
Pathology classification of cancer tumor subtypes and benign tumors can be difficult due to cellular heterogeneity and similar morphological features. Renal Cell Cancer (RCC) poses a major challenge for uropathologists as advanced RCC is often incide... read more 

MedMatch: a first step for the automation of large language model performance benchmarking for medication-related tasks

medRxiv
BackgroundThe accuracy and safety of generating medication orders by large language models (LLMs) must be demonstrated. Without standardization, performance evaluation is limited to time and resource-intensive clinician grading. This evaluation aimed... read more 

Exploring the Link Between Body Physiology and Cognition: The Role of the Brain and Ageing

medRxiv
Epidemiologists often report associations between cognitive functioning and bodily physiology in older adults, but the strength and drivers of this relationship remain unclear. Which systems - from body composition to cardiovascular, pulmonary, renal... read more 

Predicting Body Composition from Chest Radiographs by Deep Learning: 10-year Mortality and Geriatric Outcomes

medRxiv
BackgroundBody composition strongly influences clinical outcomes in older adults, yet body mass index (BMI) lacks discriminatory power, and standard tools such as bioelectrical impedance analysis (BIA), dual-energy X-ray absorptiometry are not routin... read more