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A Multimodal Approach for Early Identification of Mild Cognitive Impairment and Alzheimer's Disease With Fusion Network Using Eye Movements and Speech.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detecting Alzheimer's disease (AD) in its earliest stages, particularly during an onset of Mild Cognitive Impairment (MCI), remains challenging due to the overlap of initial symptoms with normal aging processes. Given that no cure exists and current ...

Predicting Postoperative Circulatory Complications in Older Patients: A Machine Learning Approach.

Biomedical and environmental sciences : BES
OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients.

Smart contours: deep learning-driven internal gross tumor volume delineation in non-small cell lung cancer using 4D CT maximum and average intensity projections.

Radiation oncology (London, England)
BACKGROUND: Delineating the internal gross tumor volume (IGTV) is crucial for the treatment of non-small cell lung cancer (NSCLC). Deep learning (DL) enables the automation of this process; however, current studies focus mainly on multiple phases of ...

Predicting depression and unravelling its heterogeneous influences in middle-aged and older people populations: a machine learning approach.

BMC psychology
BACKGROUND: Aging has become a global trend, and depression, as an accompanying issue, poses a significant threat to the health of middle-aged and older adults. Existing studies primarily rely on statistical methods such as logistic regression for sm...

Automated opportunistic screening for osteoporosis using deep learning-based automatic segmentation and radiomics on proximal femur images from low-dose abdominal CT.

BMC musculoskeletal disorders
RATIONALE AND OBJECTIVES: To establish an automated osteoporosis detection model based on low-dose abdominal CT (LDCT). This model combined a deep learning-based automatic segmentation of the proximal femur with a radiomics-based bone status classifi...

Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis.

Scientific reports
Hip fractures in the elderly present a significant public health challenge globally, especially among patients with hypertension, who are at an increased risk of developing preoperative deep vein thrombosis (DVT). DVT not only heightens surgical risk...

Evaluation of blood- and urine-derived biomarkers for machine learning prediction models of osteoarthritis in elderly patients: A feasibility study.

Computer methods and programs in biomedicine
BACKGROUND: Osteoarthritis (OA) is a common degenerative joint disease, particularly affecting individuals aged >50 years. It deteriorates quality of life and restricts physical activity in the elderly. Early diagnosis of OA is crucial for effective ...

Identifying the key predictors of positive self-perceptions of aging using machine learning.

Social science & medicine (1982)
This study aimed to identify key predictors of self-perceptions of aging (SPA) among older adults by examining a comprehensive set of potential predictors across physical, psychological, social, and demographic domains. Data from over 4000 American a...

A machine learning approach to differentiate stage IV from stage I colorectal cancer.

Computers in biology and medicine
BACKGROUND AND AIM: The stage at which Colorectal cancer (CRC) diagnosed is a crucial prognostic factor. Our study proposed a novel approach to aid in the diagnosis of stage IV CRC by utilizing supervised machine learning, analyzing clinical history,...

Epidemiology characteristics and clinical outcomes of composite Hodgkin lymphoma and diffuse large B-cell lymphoma using machine learning.

The oncologist
Composite lymphoma (CL) is rare. We conducted an analysis of 53 329 cases of diffuse large B-cell lymphoma (DLBCL), 17,916 cases of Hodgkin lymphoma (HL), and 869 cases of composite HL and DLBCL from the SEER database diagnosed between 2000 and 2019....