AIMC Topic: Humans

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Sepsis labels defined by claims-based methods are ill-suited for training machine learning algorithms.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases

Spontaneous perspective taking toward robots: The unique impact of humanlike appearance.

Cognition
As robots rapidly enter society, how does human social cognition respond to their novel presence? Focusing on one foundational social-cognitive capacity-visual perspective taking-seven studies reveal that people spontaneously adopt a robot's unique p...

Artificial Intelligence in Fracture Detection: A Systematic Review and Meta-Analysis.

Radiology
Background Patients with fractures are a common emergency presentation and may be misdiagnosed at radiologic imaging. An increasing number of studies apply artificial intelligence (AI) techniques to fracture detection as an adjunct to clinician diagn...

Robot-Assisted Training as Self-Training for Upper-Limb Hemiplegia in Chronic Stroke: A Randomized Controlled Trial.

Stroke
BACKGROUND: This study aimed to examine whether robotic self-training improved upper-extremity function versus conventional self-training in mild-to-moderate hemiplegic chronic stroke patients.

Machine learning-based heart disease diagnosis: A systematic literature review.

Artificial intelligence in medicine
Heart disease is one of the significant challenges in today's world and one of the leading causes of many deaths worldwide. Recent advancement of machine learning (ML) application demonstrates that using electrocardiogram (ECG) and patients' data, de...

Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program.

Radiology
Background Artificial intelligence (AI) has shown promising results for cancer detection with mammographic screening. However, evidence related to the use of AI in real screening settings remain sparse. Purpose To compare the performance of a commerc...

Artificial intelligence in perioperative medicine: a narrative review.

Korean journal of anesthesiology
Recent advancements in artificial intelligence (AI) techniques have enabled the development of accurate prediction models using clinical big data. AI models for perioperative risk stratification, intraoperative event prediction, biosignal analyses, a...