AIMC Topic: Aged

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Digital Cytology Combined With Artificial Intelligence Compared to Conventional Microscopy for Anal Cytology: A Preliminary Study.

Cytopathology : official journal of the British Society for Clinical Cytology
INTRODUCTION: Recent studies have shown that digital cytology (DC) coupled with artificial intelligence (AI) algorithms is a valid approach to the diagnosis of cervico-vaginal lesions using liquid-based cytology (LBC). We evaluated the use of these m...

Using Machine Learning Models to Diagnose Chronic Rhinosinusitis: Analysis of Pre-Treatment Patient-Generated Health Data to Predict Cardinal Symptoms and Sinonasal Inflammation.

American journal of rhinology & allergy
BackgroundThe diagnosis of chronic rhinosinusitis (CRS) relies upon patient-reported symptoms and objective nasal endoscopy and/or computed tomography (CT) findings. Many patients, at the time of evaluation by an otolaryngologist or rhinologist, lack...

PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

BMC research notes
OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bone mineral density (BMD) testing, which has limitations in early detection. This study aims to develop and validate a machine learning approach for ost...

Can some algorithms of machine learning identify osteoporosis patients after training and testing some clinical information about patients?

BMC medical informatics and decision making
OBJECTIVE: This study was designed to establish a diagnostic model for osteoporosis by collecting clinical information from patients with and without osteoporosis. Various machine learning algorithms were employed for training and testing the model, ...

Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors.

BMC musculoskeletal disorders
BACKGROUND: Periprosthetic joint infection leads to significant morbidity and mortality after total knee arthroplasty. Preoperative and perioperative risk prediction and assessment tools are lacking in Asia. This study developed the first machine lea...

Develop and validate machine learning models to predict the risk of depressive symptoms in older adults with cognitive impairment.

BMC psychiatry
BACKGROUND: Cognitive impairment and depressive symptoms are prevalent and closely interrelated mental health issues in the elderly. Traditional methods for identifying depressive symptoms in this population often lack effectiveness. Machine learning...

A comprehensive interpretable machine learning framework for mild cognitive impairment and Alzheimer's disease diagnosis.

Scientific reports
An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) by ensuring robustness of the ML models' interpretations. The dataset used comprises volumetric me...

Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand.

Scientific reports
This study aims to construct a prediction model for the demand for medical and daily care services of the elderly and to explore the factors that affect the demand for medical and daily care services of the elderly. In this study, a questionnaire sur...

AI classification of knee prostheses from plain radiographs and real-world applications.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery ...

Multimodal deep learning for predicting PD-L1 biomarker and clinical immunotherapy outcomes of esophageal cancer.

Frontiers in immunology
Although the immune checkpoint inhibitors (ICIs) have demonstrated remarkable anti-tumor efficacy in solid tumors, the proportion of ESCC patients who benefit from ICIs remains limited. Current biomarkers have assisted in identifying potential respon...