AIMC Topic: Aged, 80 and over
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Elucidating the influence of familial interactions on geriatric depression: A comprehensive nationwide multi-center investigation leveraging machine learning.
Acta psychologica
Apr 17, 2024
OBJECTIVE: A plethora of studies have unequivocally established the profound significance of harmonious familial relationships on the psychological well-being of the elderly. In this study, we elucidate the intergenerational relationships, probing th...
Differentiating ischemic stroke patients from healthy subjects using a large-scale, retrospective EEG database and machine learning methods.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 16, 2024
OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-min resting electroencephalogram (EEG) recording from which featu...
Diagnosis, Differential
Predictive Value of Tests
Ischemic Stroke
Electroencephalography
Signal Processing, Computer-Assisted
Machine Learning
Reproducibility of Results
Male
Brain Waves
Aged
Databases, Factual
Middle Aged
Aged, 80 and over
Brain
Case-Control Studies
Adult
Retrospective Studies
Diagnosis, Computer-Assisted
Humans
Female
Time Factors
Development and Internal Validation of a Multivariable Prediction Model for Mortality After Hip Fracture with Machine Learning Techniques.
Calcified tissue international
Apr 16, 2024
In order to estimate the likelihood of 1, 3, 6 and 12 month mortality in patients with hip fractures, we applied a variety of machine learning methods using readily available, preoperative data. We used prospectively collected data from a single univ...
Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning.
Nature medicine
Apr 16, 2024
Cancer of unknown primary (CUP) site poses diagnostic challenges due to its elusive nature. Many cases of CUP manifest as pleural and peritoneal serous effusions. Leveraging cytological images from 57,220 cases at four tertiary hospitals, we develope...
Fall prediction in a quiet standing balance test via machine learning: Is it possible?
PloS one
Apr 16, 2024
The elderly population is growing rapidly in the world and falls are becoming a big problem for society. Currently, clinical assessments of gait and posture include functional evaluations, objective, and subjective scales. They are considered the gol...
An Automated Multi-scale Feature Fusion Network for Spine Fracture Segmentation Using Computed Tomography Images.
Journal of imaging informatics in medicine
Apr 15, 2024
Spine fractures represent a critical health concern with far-reaching implications for patient care and clinical decision-making. Accurate segmentation of spine fractures from medical images is a crucial task due to its location, shape, type, and sev...
Completion of Pembrolizumab in Advanced Non-Small Cell Lung Cancer-Real World Outcomes After Two Years of Therapy (COPILOT).
Clinical lung cancer
Apr 15, 2024
BACKGROUND: Seminal trials with first-line pembrolizumab for metastatic non-small cell lung cancer (NSCLC) mandated a maximum two-years treatment. We describe real-world outcomes of a multi-site Australian cohort of patients who completed two-years o...
Higher blood biochemistry-based biological age developed by advanced deep learning techniques is associated with frailty in geriatric rehabilitation inpatients: RESORT.
Experimental gerontology
Apr 13, 2024
BACKGROUND: Accelerated biological ageing is a major underlying mechanism of frailty development. This study aimed to investigate if the biological age measured by a blood biochemistry-based ageing clock is associated with frailty in geriatric rehabi...
Deep learning for the automatic detection and segmentation of parotid gland tumors on MRI.
Oral oncology
Apr 13, 2024
OBJECTIVES: Parotid gland tumors (PGTs) often occur as incidental findings on magnetic resonance images (MRI) that may be overlooked. This study aimed to construct and validate a deep learning model to automatically identify parotid glands (PGs) with...
Development and validation of machine learning models to predict frailty risk for elderly.
Journal of advanced nursing
Apr 11, 2024
AIMS: Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to pred...
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