AIMC Topic: Aged

Clear Filters Showing 21 to 30 of 14227 articles

Bridging Gaps in Women's Heart Health: User-Centered Needs Assessment Informed by Patient and Clinician Interviews.

JMIR human factors
BACKGROUND: Women with cardiovascular disease (CVD) remain underserved due to gaps in recognition, diagnosis, and care tailored to sex-specific risks. Digital health tools have the potential to address these inequities, but many fail to reflect the d...

Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset.

JMIR cancer
BACKGROUND: Metastatic cancer remains one of the leading causes of cancer-related mortality worldwide. Yet, the prediction of survivability in this population remains limited by heterogeneous clinical presentations and high-dimensional molecular feat...

Neutrophil Percentage-to-Albumin Ratio as a Novel Prognostic Biomarker in Adult Diffuse Gliomas: Retrospective Study Integrating 3 Machine Learning Models and Cox Regression.

JMIR medical informatics
BACKGROUND: Adult-type diffuse glioma (ADG) is the most common primary malignant tumor of the central nervous system. Its highly invasive nature, marked heterogeneity, and resistance to therapy contribute to a high risk of recurrence and poor prognos...

Large Language Models for Psychiatric Diagnosis Based on Multicenter Real-World Clinical Records: Comparative Study.

JMIR medical informatics
BACKGROUND: Psychiatric disorders are diagnostically challenging and often rely on subjective clinical judgment, particularly in resource-limited settings. Large language models (LLMs) have demonstrated potential in supporting psychiatric diagnosis; ...

CTA-based deep-learning integrated model for identifying irregular shape and aneurysm size of unruptured intracranial aneurysms.

Journal of neurointerventional surgery
BACKGROUND: Artificial intelligence can help to identify irregular shapes and sizes, crucial for managing unruptured intracranial aneurysms (UIAs). However, existing artificial intelligence tools lack reliable classification of UIA shape irregularity...

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...

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...

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...

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...