AIMC Topic: Aged

Clear Filters Showing 401 to 410 of 12425 articles

Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care.

BMC medicine Apr 30, 2025
BACKGROUND: The aim of our study was to determine whether the application of machine learning could predict PASC by using diagnoses from primary care and prescribed medication 1 year prior to PASC diagnosis.
Young Adult Humans Risk Assessment Adult SARS-CoV-2 Machine Learning Case-Control Studies Male Sweden COVID-19 Adolescent Middle Aged Risk Factors Female Primary Health Care Hospitalization Post-Acute COVID-19 Syndrome Aged
View on PubMed DOI

Machine learning-based prediction of postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy.

BMC surgery Apr 30, 2025
BACKGROUND: Clinically relevant postoperative pancreatic fistula (CR-POPF) following laparoscopic pancreaticoduodenectomy (LPD) is a critical complication that significantly worsens patient outcomes. However, the heterogeneity of its risk factors and...
Risk Factors Risk Assessment Humans Aged Postoperative Complications Machine Learning Adult Laparoscopy Retrospective Studies Male Female Pancreatic Fistula Middle Aged Pancreaticoduodenectomy
View on PubMed DOI

Exploring the potential of machine learning in gastric cancer: prognostic biomarkers, subtyping, and stratification.

BMC cancer Apr 30, 2025
BACKGROUND: Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biomarkers in GC prognosis. Machine-learning (ML)-based methods can be applied to identify the most impo...
Ki-67 Antigen Matrix Metalloproteinase 7 Humans Machine Learning Middle Aged Prognosis Principal Component Analysis Female Neoplasm Staging Aged Vimentin Adult Tumor Suppressor Protein p53 Stomach Neoplasms Biomarkers, Tumor Male
View on PubMed DOI

Factors influencing short-term and long-term survival rates in stroke patients receiving enteral nutrition: a machine learning approach using MIMIC-IV database.

BMC neurology Apr 30, 2025
PURPOSE: This study aims to evaluate the survival and mortality rates of stroke patients after receiving enteral nutrition, and to explore factors influencing long-term survival. With an aging society, nutritional management of stroke patients has be...
Humans Machine Learning Databases, Factual Female Aged Aged, 80 and over Survival Rate Male Middle Aged Stroke Kaplan-Meier Estimate Enteral Nutrition
View on PubMed DOI

Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.

JMIR aging Apr 30, 2025
BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. T...
Aged Aged, 80 and over Male China Humans Cognitive Dysfunction Longitudinal Studies Machine Learning East Asian People Prospective Studies Longevity Biomarkers Female
View on PubMed DOI

Harnessing an Artificial Intelligence-Based Large Language Model With Personal Health Record Capability for Personalized Information Support in Postsurgery Myocardial Infarction: Descriptive Qualitative Study.

Journal of medical Internet research Apr 30, 2025
BACKGROUND: Myocardial infarction (MI) remains a leading cause of morbidity and mortality worldwide. Although postsurgical cardiac interventions have improved survival rates, effective management during recovery remains challenging. Traditional infor...
Large Language Models Male Middle Aged Qualitative Research Health Records, Personal Precision Medicine Myocardial Infarction Language Humans Female Artificial Intelligence Aged
View on PubMed DOI

Tumor grade-titude: XGBoost radiomics paves the way for RCC classification.

European journal of radiology Apr 29, 2025
This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT images to differentiate grade 4 renal cell carcinoma (RCC) from lower-grade tumours. A total of 102 R...
Reproducibility of Results Aged Aged, 80 and over Adult Sensitivity and Specificity Humans Machine Learning Tomography, X-Ray Computed Female Neoplasm Grading Radiographic Image Interpretation, Computer-Assisted Kidney Neoplasms Carcinoma, Renal Cell Boosting Machine Learning Algorithms Radiomics Male Middle Aged Contrast Media
View on PubMed DOI

A machine learning tool for prediction of vertebral compression fracture following stereotactic body radiation therapy for spinal metastases.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Apr 29, 2025
BACKGROUND AND PURPOSE: The most common adverse event following spine stereotactic body radiotherapy (SBRT) is vertebral compression fracture (VCF). There is interest in the development of patient-specific tools that can predict those at high risk of...
Radiosurgery Spinal Fractures Fractures, Compression Humans Machine Learning Aged Aged, 80 and over Male Middle Aged Spinal Neoplasms Retrospective Studies Female Risk Factors
View on PubMed DOI

Clinical Validation of a Noninvasive Multi-Omics Method for Multicancer Early Detection in Retrospective and Prospective Cohorts.

The Journal of molecular diagnostics : JMD Apr 29, 2025
Recent studies highlight the promise of blood-based multicancer early detection (MCED) tests for identifying asymptomatic patients with cancer. However, most focus on a single cancer hallmark, thus limiting effectiveness because of cancer's heterogen...
Algorithms Prospective Studies Retrospective Studies Female Aged Humans Neoplasms Genomics Multiomics Early Detection of Cancer Adult Whole Genome Sequencing Sensitivity and Specificity Biomarkers, Tumor Male Middle Aged
View on PubMed DOI

Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.

The international journal of cardiovascular imaging Apr 29, 2025
Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF) patients, but data analysis requires time-consuming anatomical contouring for many cardiac time frames. Our goal was to develop a convolutional neura...
Image Interpretation, Computer-Assisted Observer Variation Automation Blood Flow Velocity Atrial Function, Left Predictive Value of Tests Atrial Fibrillation Heart Atria Heart Rate Magnetic Resonance Imaging, Cine Humans Female Reproducibility of Results Aged Male Middle Aged Deep Learning Time Factors Magnetic Resonance Imaging
View on PubMed DOI
Popular Topics
Recent Journals