AIMC Topic: Humans

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Effectiveness of robot-assisted training in adults with Parkinson's disease: a systematic review and meta-analysis.

Journal of neurology
AIM: This work aimed to update and summarize the existing evidence on the effectiveness of robot-assisted training (RAT) in adults with Parkinson's disease (PD).

The roles of cognitive dissonance and normative reasoning in attributions of minds to robots.

Cognitive research: principles and implications
As a wide variety of intelligent technologies become part of everyday life, researchers have explored how people conceptualize agents that in some ways act and think like living things but are clearly machines. Much of this work draws upon the idea t...

Early specialization in formative basketball: A machine learning analysis of shooting patterns in U14 and professional players.

Journal of sports sciences
Growing evidence supports that early sport specialization in children and adolescents may compromise long-term athlete development and high-performance acquisition. This study aimed to determine the presence of specialised shooting roles in formative...

Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach.

Renal failure
BACKGROUND: Acute kidney injury (AKI) and acute kidney disease (AKD) are prevalent among pediatric patients, both linked to increased mortality and extended hospital stays. Early detection of kidney injury is crucial for improving outcomes. This stud...

Development and Clinical Validation of Visual Inspection With Acetic Acid Application-Artificial Intelligence Tool Using Cervical Images in Screen-and-Treat Visual Screening for Cervical Cancer in South India: A Pilot Study.

JCO global oncology
PURPOSE: The burden of cervical cancer in India is enormous, with more than 60,000 deaths being reported in 2020. The key intervention in the WHO's global strategy for the elimination of cervical cancer is to aim for the treatment and care of 90% of ...

The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model.

Frontiers in immunology
BACKGROUND: Sepsis is a life-threatening organ dysfunction condition produced by dysregulation of the host response to infection. It is now characterized by a high clinical morbidity and mortality rate, endangering patients' lives and health. The pur...

Genotype-negative multiple endocrine neoplasia type 1 with prolactinoma, hyperparathyroidism, and subclinical Cushing's syndrome accompanied by hyperglycemia: a case report.

Frontiers in endocrinology
BACKGROUND: Multiple endocrine neoplasia type 1 (MEN1) is a rare autosomal dominant disorder, accompanied by multiple endocrine neoplasms of the parathyroid, pancreas, pituitary, and other neoplasms in the adrenal glands. However, in some cases, pati...

Cross-disease transcriptomic analysis reveals DOK3 and PAPOLA as therapeutic targets for neuroinflammatory and tumorigenic processes.

Frontiers in immunology
OBJECTIVE: Subarachnoid hemorrhage (SAH) and tumorigenesis share numerous biological complexities; nevertheless, the specific gene expression profiles and underlying mechanisms remain poorly understood. This study aims to identify differentially expr...

Systematic evaluation of machine learning models for postoperative surgical site infection prediction.

PloS one
BACKGROUND: Surgical site infections (SSIs) lead to increased mortality and morbidity, as well as increased healthcare costs. Multiple models for the prediction of this serious surgical complication have been developed, with an increasing use of mach...

Advanced susceptibility analysis of ground deformation disasters using large language models and machine learning: A Hangzhou City case study.

PloS one
To address the prevailing scenario where comprehensive susceptibility assessments of ground deformation disasters primarily rely on knowledge-driven models, with weight judgments largely founded on expert subjective assessments, this study initially ...