AIMC Topic: Female

Clear Filters Showing 61 to 70 of 29210 articles

Predicting symptomatic intracranial hemorrhage after endovascular treatment of vertebrobasilar artery occlusion: PEACE score.

Journal of neurointerventional surgery
BACKGROUND: Current clinical decision tools for assessing the risk of symptomatic intracranial hemorrhage (sICH) in patients with vertebrobasilar artery occlusion (VBAO) who received endovascular treatment (EVT) have limited performance. This study d...

Workflow improvements from automated large vessel occlusion detection algorithms are dependent on care team engagement.

Journal of neurointerventional surgery
BACKGROUND: Automated machine learning (ML)-based large vessel occlusion (LVO) detection algorithms have been shown to improve in-hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction a...

Evaluating Spanish Translations of Emergency Department Discharge Instructions by a Large Language Model: Tool Validation and Reliability Study.

JMIR formative research
When given a sample of 100 emergency department discharge instructions, Claude Sonnet, a large language model, produced accurate Spanish translations as evaluated by Spanish-speaking physicians and medical interpreters.

Key Information Influencing Patient Decision-Making About AI in Health Care: Survey Experiment Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI)-enabled devices are increasingly used in health care. However, there has been limited research on patients' informational preferences, including which elements of AI device labeling enhance patient understandi...

AI-driven peptide discovery for endometrial cancer: deep generative modeling and molecular simulation in the big data era.

Journal of computer-aided molecular design
The integration of artificial intelligence (AI) with molecular modeling offers new opportunities to accelerate therapeutic discovery. In this study, we developed an AI-driven generative pipeline combining deep reinforcement learning (DRL), generative...

A geometric shape regularity effect in the human brain.

eLife
The perception and production of regular geometric shapes, a characteristic trait of human cultures since prehistory, has unknown neural mechanisms. Behavioral studies suggest that humans are attuned to discrete regularities such as symmetries and pa...

Automated vertigo diagnosis using video-oculography and artificial intelligence for clinic-based triage: Preliminary results.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Distinguishing dangerous from benign vertigo remains a diagnostic challenge. Our study aimed to develop and evaluate a machine learning model to differentiate between dangerous and benign vertigo in the outpatient setting across two medic...

Irritable bowel syndrome-specific volatile organic compounds in faecal headspace do not associate with classical symptom-based subtypes.

Journal of breath research
Irritable bowel syndrome (IBS), a disorder of gut-brain interaction, is diagnosed using symptom-based Rome criteria. These criteria classify IBS patients into four subtypes in accordance to their stool patterns. However, whether this subtyping approa...

Dynamic thumb localization and its adaptation: quantification with a novel robotic task.

Experimental brain research
The thumb plays a crucial role in hand function, yet its proprioceptive abilities remain poorly understood. Here we quantified dynamic thumb localization ability, as well as how this ability adapts to a perturbation, in unimpaired participants. For t...

Machine Learning Analysis of Retrospective Data From 503 Hospitalized Older Patients With Type 2 Diabetes to Identify Factors Associated With Cognitive Impairment.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Diabetes is increasingly prevalent among older adults; mild cognitive impairment (MCI) comorbidity in this group represents a major concern. Existing MCI prediction methods are often inaccurate, but machine learning (ML) offers improved po...