AIMC Topic: Humans

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Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data.

BMJ health & care informatics
OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep clustering methodology that combines supervised and unsupervised machine learning.

Improving AI-Based Clinical Decision Support Systems and Their Integration Into Care From the Perspective of Experts: Interview Study Among Different Stakeholders.

JMIR medical informatics
BACKGROUND: Artificial intelligence (AI)-based systems are receiving increasing attention in the health care sector. While the use of AI is well advanced in some medical applications, such as image recognition, it is still in its infancy in others, s...

Quantitative Research on Digitalized Treatment Options for Older Adults With Mental Illness: Scoping Review.

JMIR mental health
BACKGROUND: Older adults with mental illness face specific physical and psychosocial challenges and inequities, reflected in limited access to advanced technology. This digital divide is alarming as mental health interventions increasingly depend on ...

Scalable Precision Psychiatry With an Objective Measure of Psychological Stress: Prospective Real-World Study.

Journal of medical Internet research
BACKGROUND: Before meaningful progress toward precision psychiatry is possible, objective (unbiased) assessment of patient mental well-being must be validated and adopted broadly.

Artificial Intelligence-Enabled Point-of-Care Echocardiography: Bringing Precision Imaging to the Bedside.

Current atherosclerosis reports
PURPOSE OF REVIEW: The integration of artificial intelligence (AI) with point-of-care ultrasound (POCUS) is transforming cardiovascular diagnostics by enhancing image acquisition, interpretation, and workflow efficiency. These advancements hold promi...

External validation of a prediction model for disability and pain after lumbar disc herniation surgery: a prospective international registry-based cohort study.

Acta orthopaedica
BACKGROUND AND PURPOSE:  We aimed to externally validate machine learning models developed in Norway by evaluating their predictive outcome of disability and pain 12 months after lumbar disc herniation surgery in a Swedish and Danish cohort.

Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cases.

Acta orthopaedica
BACKGROUND AND PURPOSE:  Treatment-related shared decision-making (SDM) in older adults with hip fractures is complex due to the need to balance patient-specific factors such as life goals, frailty, and surgical risks. It includes considerations such...

Novel 59-layer dense inception network for robust deepfake identification.

Scientific reports
The exponential growth of Artificial Intelligence (AI) has led to the emergence of cutting edge methods and a plethora of new tools for media editing. The use of these tools has also facilitated the spread of false information, propaganda, and harass...

Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study.

Military Medical Research
BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) has significantly advanced prostate cancer (PCa) detection, yet decisions on invasive biopsy with moderate prostate imaging reporting and data system (PI-RADS) scores remain ambiguous.

It is not about autonomy: realigning the ethical debate on substitute judgement and AI preference predictors in healthcare.

Journal of medical ethics
This article challenges two dominant assumptions in the current ethical debate over the use of algorithmic Personalised Patient Preference Predictors (P4) in substitute judgement for incapacitated patients. First, I question the belief that the auton...