AIMC Topic: Aged

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Implementation of Fully Automated AI-Integrated System for Body Composition Assessment on Computed Tomography for Opportunistic Sarcopenia Screening: Multicenter Prospective Study.

JMIR formative research
BACKGROUND: Opportunistic computed tomography (CT) screening for the evaluation of sarcopenia and myosteatosis has been gaining emphasis. A fully automated artificial intelligence (AI)-integrated system for body composition assessment on CT scans is ...

Proposition of a new, minimally-invasive, software smartphone device to predict sleep apnea and its severity.

Sleep & breathing = Schlaf & Atmung
PURPOSE: obstructive sleep apnea is underdiagnosed due to limited access to polysomnography (PSG). We aimed to assess the performances of Apneal, an application recording sound and movements thanks to a smartphone's microphone, accelerometer and gyro...

Interpretable machine learning model predicts 1-year inguinal hernia risk after robot-assisted radical prostatectomy.

Journal of robotic surgery
Inguinal hernia represents a clinically significant yet underreported complication of robot-assisted radical prostatectomy (RARP) for localized prostate cancer, with a notably high incidence within the first postoperative year. Despite its adverse im...

AI-driven bone mineral density prediction from chest x-rays and its association with obstructive sleep apnea.

PloS one
With an increasing aging population, the prevalence of chronic comorbidities is on the rise. The potential relationship between obstructive sleep apnea (OSA) and osteoporosis has garnered significant attention. Most studies examining the association ...

Utilisation of AI-driven chatbots for perioperative health information seeking: a descriptive qualitative study of orthopaedic patients and family members.

BMJ open
OBJECTIVE: This study aimed to explore orthopaedic patients' and families' experiences with artificial intelligence (AI)-driven chatbots for perioperative health information, focusing on usability, effectiveness and perceptions.

Machine learning predictions of unplanned readmissions using electronic medical records: Predictor importance across medical and surgical patient populations.

PloS one
Hospital readmissions prolong patient suffering and increase healthcare expenditures. While several studies have attempted to develop prediction models to reduce readmissions, most have demonstrated modest predictive accuracy. To improve upon prior a...

Data-driven identification of key predictors of uncontrolled hypertension: A cross-sectional study.

PloS one
Uncontrolled hypertension (HTN) increases the risk of adverse health events. This study aimed to identify key predictors of uncontrolled HTN in 1,308 Mexican adults with a prior diagnosis of HTN who were undergoing pharmacological treatment. We utili...

Breast cancer classification based on the integration of diagnostic algorithms for calcifications and masses using a mixture of experts.

PloS one
PURPOSE: To investigate the effectiveness of an integrated deep-learning (DL) algorithm, the Mixture of Radiological Findings Specific Experts (MoRFSE), in breast cancer classification by imitating the diagnostic decision-making process of radiologis...

KPNA2 expression as a biomarker for immunosuppressive microenvironment predicting response to TKI and immunotherapy in metastatic renal cell carcinoma.

European journal of pharmacology
BACKGROUND: Immunotherapy (IO) combined with tyrosine kinase inhibitors (TKI) are now first-line therapy for advanced renal cell carcinoma (RCC), though reliable predictive biomarkers remain elusive. Recent evidence demonstrates that karyopherin α2 s...