AIMC Topic: Aged

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Stitched vision transformer for age-related macular degeneration detection using retinal optical coherence tomography images.

PloS one Jun 5, 2024
Age-related macular degeneration (AMD) is an eye disease that leads to the deterioration of the central vision area of the eye and can gradually result in vision loss in elderly individuals. Early identification of this disease can significantly impa...
Aged Humans Neural Networks, Computer Algorithms Tomography, Optical Coherence Retina Macular Degeneration
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Applying machine learning to construct an association model for lung cancer and environmental hormone high-risk factors and nursing assessment reconstruction.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing Jun 4, 2024
INTRODUCTION: To utilize machine learning techniques to develop an association model linking lung cancer and environmental hormones to enhance the understanding of potential lung cancer risk factors and refine current nursing assessments for lung can...
Lung Neoplasms Environmental Exposure Cadmium Nursing Assessment Risk Factors Aged Male Middle Aged Humans Machine Learning Female
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An ethical assessment of professional opinions on concerns, chances, and limitations of the implementation of an artificial intelligence-based technology into the geriatric patient treatment and continuity of care.

GeroScience Jun 4, 2024
With the introduction of an artificial intelligence-based dashboard into the clinic, the project SURGE-Ahead responds to the importance of improving perioperative geriatric patient treatment and continuity of care. The use of artificial intelligence ...
Humans Artificial Intelligence Geriatrics Female Attitude of Health Personnel Physician-Patient Relations Aged Continuity of Patient Care Male Qualitative Research
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Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

Abdominal radiology (New York) Jun 4, 2024
OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm.
Algorithms Retrospective Studies Tomography, X-Ray Computed Female Humans Machine Learning Radiographic Image Interpretation, Computer-Assisted Feasibility Studies Neoplasm Recurrence, Local Esophageal Neoplasms Aged Aged, 80 and over Male Predictive Value of Tests
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A Novel Machine Learning Model for Predicting Stroke-Associated Pneumonia After Spontaneous Intracerebral Hemorrhage.

World neurosurgery Jun 4, 2024
BACKGROUND: Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there...
Machine Learning Cerebral Hemorrhage Prognosis Pneumonia Humans Predictive Value of Tests Retrospective Studies Aged Stroke Female Aged, 80 and over Male Middle Aged
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Pleiotropic Effects of Direct Oral Anticoagulants in Chronic Heart Failure and Atrial Fibrillation: Machine Learning Analysis.

Molecules (Basel, Switzerland) Jun 4, 2024
Oral anticoagulant therapy (OAT) for managing atrial fibrillation (AF) encompasses vitamin K antagonists (VKAs, such as warfarin), which was the mainstay of anticoagulation therapy before 2010, and direct-acting oral anticoagulants (DOACs, namely dab...
Heart Failure Humans Administration, Oral Atrial Fibrillation Machine Learning Male Female Chronic Disease Aged Anticoagulants Warfarin
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Effects of robot-assisted upper limb training combined with functional electrical stimulation in stroke patients: study protocol for a randomized controlled trial.

Trials Jun 4, 2024
INTRODUCTION: About 17-80% stroke survivors experience the deficit of upper limb function, which strongly influences their independence and quality of life. Robot-assisted training and functional electrical stimulation are commonly used interventions...
Humans Female Aged Adult Stroke Rehabilitation Single-Blind Method Stroke Combined Modality Therapy Treatment Outcome Exercise Therapy Activities of Daily Living Recovery of Function Male Randomized Controlled Trials as Topic Hemiplegia Middle Aged Robotics Upper Extremity Quality of Life Electric Stimulation Therapy Time Factors
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Development and external validation of a machine learning model for the prediction of persistent acute kidney injury stage 3 in multi-centric, multi-national intensive care cohorts.

Critical care (London, England) Jun 4, 2024
BACKGROUND: The aim of this retrospective cohort study was to develop and validate on multiple international datasets a real-time machine learning model able to accurately predict persistent acute kidney injury (AKI) in the intensive care unit (ICU).
Aged Adult Male Middle Aged Cohort Studies ROC Curve Retrospective Studies Acute Kidney Injury Intensive Care Units Female Humans Machine Learning
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Prediction of subsequent fragility fractures: application of machine learning.

BMC musculoskeletal disorders Jun 4, 2024
BACKGROUND: Machine learning (ML) has shown exceptional promise in various domains of medical research. However, its application in predicting subsequent fragility fractures is still largely unknown. In this study, we aim to evaluate the predictive p...
Risk Factors Aged Aged, 80 and over Male Algorithms Retrospective Studies Osteoporosis Female Middle Aged Risk Assessment Predictive Value of Tests Osteoporotic Fractures Humans Machine Learning
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Fairer AI in ophthalmology via implicit fairness learning for mitigating sexism and ageism.

Nature communications Jun 4, 2024
The transformative role of artificial intelligence (AI) in various fields highlights the need for it to be both accurate and fair. Biased medical AI systems pose significant potential risks to achieving fair and equitable healthcare. Here, we show an...
Ageism Sexism Artificial Intelligence Female Aged Adult Humans Male Middle Aged Ophthalmology Eye Diseases
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