AIMC Topic: Aged

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Generation of surgical reports for lymph node dissection during laparoscopic gastric cancer surgery based on artificial intelligence.

International journal of computer assisted radiology and surgery
PURPOSE: This study aimed to develop an artificial intelligence (AI) model for the surgical report output of laparoscopic lymph node dissection in the suprapancreatic region during gastric cancer surgery.

Clinical Trial Notifications Triggered by Artificial Intelligence-Detected Cancer Progression: A Randomized Trial.

JAMA network open
IMPORTANCE: Historically, fewer than 10% of adults with cancer have enrolled in clinical trials. Computational tools have been developed to match patients to trials, but these tools are relevant only when patients need new treatment.

Perspectives on AI and Novel Technologies Among Older Adults, Clinicians, Payers, Investors, and Developers.

JAMA network open
IMPORTANCE: Artificial intelligence (AI) and novel technologies, such as remote sensors, robotics, and decision support algorithms, offer the potential for improving the health and well-being of older adults, but the priorities of key partners across...

Identifying chemotherapy beneficiaries in nasal and paranasal sinus cancers: epidemiological trends and machine learning insights.

European journal of medical research
BACKGROUND: Studies on the epidemiological characteristics, treatment strategies and prognosis of nasal and paranasal sinus cancer are still relatively limited.

Geriatric and gerontological physiotherapy in focus: a cross-sectional survey of education, clinical practice, and service availability across world physiotherapy member nations.

BMC medical education
BACKGROUND: The ageing global population necessitates specialised geriatric/gerontological physiotherapy services (GPTS) to address age-related conditions. We explored the current state of geriatric/gerontological physiotherapy (GPT) academic program...

Detecting cognitive impairment in cerebrovascular disease using gait, dual tasks, and machine learning.

BMC medical informatics and decision making
BACKGROUND: Cognitive impairment is common after a stroke, but it can often go undetected. In this study, we investigated whether using gait and dual tasks could help detect cognitive impairment after stroke.

Comparative analysis of deep learning architectures for thyroid eye disease detection using facial photographs.

BMC ophthalmology
PURPOSE: To compare two artificial intelligence (AI) models, residual neural networks ResNet-50 and ResNet-101, for screening thyroid eye disease (TED) using frontal face photographs, and to test these models under clinical conditions.

AI-based detection and classification of anomalous aortic origin of coronary arteries using coronary CT angiography images.

Nature communications
Anomalous aortic origin of the coronary artery (AAOCA) is a rare cardiac condition that can lead to ischemia or sudden cardiac death, yet it is often overlooked or falsely classified in routine coronary CT angiography (CCTA). Here, we developed, vali...

Emerging Models of Care Using IT in Long-Term/Post-Acute Care: A Comparative Analysis of Human and AI-Driven Qualitative Insights.

Journal of gerontological nursing
PURPOSE: As the global population ages, long-term/post-acute care (LTPAC) systems face challenges in ensuring quality care for older adults with complex medical needs. Using health information technology (IT) is a promising strategy to address these ...

Gender Differences in Predicting Metabolic Syndrome Among Hospital Employees Using Machine Learning Models: A Population-Based Study.

The journal of nursing research : JNR
BACKGROUND: Metabolic syndrome (MetS) is a complex condition that captures several markers of dysregulation, including obesity, elevated blood glucose levels, dyslipidemia and hypertension. Using an approach to early prediction of MetS risk in hospit...