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Optimizing ICU Care: Machine Learning and PCA for Early Prediction of Renal Replacement Therapy Requirement.

Studies in health technology and informatics Aug 22, 2024
Forecasting the need for Renal Replacement Therapy (RRT) in intensive care units (ICUs) at an early stage can enhance patient outcomes and optimize resource allocation. The study aimed to develop a model for early prediction of Renal Replacement Ther...
Intensive Care Units Male Principal Component Analysis Critical Care Humans Machine Learning Renal Replacement Therapy
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Advancing Cardiovascular Mortality Trend Analysis: A Machine Learning Approach to Predict Future Health Policy Needs.

Studies in health technology and informatics Aug 22, 2024
This study investigates the forecasting of cardiovascular mortality trends in Greece's elderly population. Utilizing mortality data from 2001 to 2020, we employ two forecasting models: the Autoregressive Integrated Moving Average (ARIMA) and Facebook...
Health Policy Humans Female Models, Statistical Machine Learning Aged Greece Forecasting Male Cardiovascular Diseases
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Machine Learning to Predict the Risk of Malnutrition in Hospitalized Patients with Pneumonia and Analysis of Related Prognostic Factor.

Studies in health technology and informatics Aug 22, 2024
This study explored machine learning's potential in predicting the nutritional status and outcomes for pneumonia patients. It focused on 4,368 patients in a Taiwan medical center from Jan 2016 to Feb 2022, excluding ICU cases. The average age was 77....
Malnutrition Humans Machine Learning Prognosis Female Hospitalization Aged Aged, 80 and over Male Risk Assessment Length of Stay Taiwan Pneumonia
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Machine Learning-Based Predictive Models for Early Detection of Cardiovascular Diseases: A Study Utilizing Patient Samples from a Tertiary Health Promotion Center in Korea.

Studies in health technology and informatics Aug 22, 2024
A machine learning model was developed for cardiovascular diseases prediction based on 21,118 patient checkups data from a tertiary medical institution in Seoul, Korea, collected between 2009 and 2021. XGBoost algorithm showed the highest predictive ...
Cardiovascular Diseases Middle Aged Health Promotion Tertiary Care Centers Early Diagnosis Algorithms Humans Republic of Korea Machine Learning Female Male
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Initial Investigations into Physician Acceptance of Medical AI: Examining Trust, Resistance, Perceived Job Insecurity, and Usage Intentions.

Studies in health technology and informatics Aug 22, 2024
This study evaluated physicians' attitudes towards medical AI across three Taiwanese hospitals, focusing on constructs of trust, resistance, job insecurity, and adoption willingness, with a survey based on the Dual-factor Model yielding 282 responses...
Humans Artificial Intelligence Taiwan Intention Attitude to Computers Job Security Male Physicians Trust Female Surveys and Questionnaires Adult Attitude of Health Personnel
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Machine Learning with Clinical and Intraoperative Biosignal Data for Predicting Cardiac Surgery-Associated Acute Kidney Injury.

Studies in health technology and informatics Aug 22, 2024
Early identification of patients at high risk of cardiac surgery-associated acute kidney injury (CSA-AKI) is crucial for its prevention. We aimed to leverage perioperative clinical and intraoperative biosignal data to develop machine learning models ...
Middle Aged Postoperative Complications Monitoring, Intraoperative Cardiac Surgical Procedures Female Aged Male Humans Machine Learning Biomarkers Acute Kidney Injury
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Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer.

Studies in health technology and informatics Aug 22, 2024
Prostate cancer is a dominant health concern calling for advanced diagnostic tools. Utilizing digital pathology and artificial intelligence, this study explores the potential of 11 deep neural network architectures for automated Gleason grading in pr...
Humans Neural Networks, Computer Male Deep Learning Prostatic Neoplasms Neoplasm Grading Image Interpretation, Computer-Assisted
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Prediction of Poor Glycemic Control in Children with Type 1 Diabetes.

Studies in health technology and informatics Aug 22, 2024
This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.
Male Adolescent Blood Glucose Child, Preschool Humans Machine Learning Female Child Diabetes Mellitus, Type 1 Glycated Hemoglobin Glycemic Control
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Harnessing the Power of Machine Learning and Electronic Health Records to Support Child Abuse and Neglect Identification in Emergency Department Settings.

Studies in health technology and informatics Aug 22, 2024
Emergency departments (EDs) are pivotal in detecting child abuse and neglect, but this task is often complex. Our study developed a machine learning model using structured and unstructured electronic health record (EHR) data to predict when children ...
Humans Machine Learning Algorithms Electronic Health Records Emergency Service, Hospital Child Abuse Case-Control Studies Child, Preschool Child Female Natural Language Processing Male Infant
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Patient-led skin cancer teledermatology without dermoscopy during the COVID-19 pandemic: important lessons for the development of future patient-facing teledermatology and artificial intelligence-assisted -self-diagnosis.

Clinical and experimental dermatology Aug 22, 2024
MySkinSelfie is a mobile phone application for skin self-monitoring, enabling secure sharing of patient-captured images with healthcare providers. This retrospective study assessed MySkinSelfie's role in remote skin cancer assessment at two centres f...
Carcinoma, Squamous Cell Humans Dermoscopy SARS-CoV-2 Artificial Intelligence Aged COVID-19 Telemedicine Melanoma Adult Retrospective Studies Dermatology Skin Neoplasms Male Female Referral and Consultation Carcinoma, Basal Cell Middle Aged Remote Consultation Mobile Applications
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