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Convolutional neural network based detection of early stage Parkinson's disease using the six minute walk test.
Scientific reports
Sep 30, 2024
The heterogeneity of Parkinson's disease (PD) presents considerable challenges for accurate diagnosis, particularly during early-stage disease, when the symptoms may be extremely subtle. This study aimed to assess the accuracy of a convolutional neur...
Enhancing severe hypoglycemia prediction in type 2 diabetes mellitus through multi-view co-training machine learning model for imbalanced dataset.
Scientific reports
Sep 30, 2024
Patients with type 2 diabetes mellitus (T2DM) who have severe hypoglycemia (SH) poses a considerable risk of long-term death, especially among the elderly, demanding urgent medical attention. Accurate prediction of SH remains challenging due to its m...
Enhancing Performance of the National Field Triage Guidelines Using Machine Learning: Development of a Prehospital Triage Model to Predict Severe Trauma.
Journal of medical Internet research
Sep 30, 2024
BACKGROUND: Prehospital trauma triage is essential to get the right patient to the right hospital. However, the national field triage guidelines proposed by the American College of Surgeons have proven to be relatively insensitive when identifying se...
Identifying the Severity of Heart Valve Stenosis and Regurgitation Among a Diverse Population Within an Integrated Health Care System: Natural Language Processing Approach.
JMIR cardio
Sep 30, 2024
BACKGROUND: Valvular heart disease (VHD) is a leading cause of cardiovascular morbidity and mortality that poses a substantial health care and economic burden on health care systems. Administrative diagnostic codes for ascertaining VHD diagnosis are ...
Machine learning and biological validation identify sphingolipids as potential mediators of paclitaxel-induced neuropathy in cancer patients.
eLife
Sep 30, 2024
BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is a serious therapy-limiting side effect of commonly used anticancer drugs. Previous studies suggest that lipids may play a role in CIPN. Therefore, the present study aimed to identify th...
Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.
Frontiers in immunology
Sep 30, 2024
BACKGROUNDS: During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the disease has placed an enormous burden on the world's healthcare and economy. The early risk assessment system based on a variety of machine learning (ML) ...
Diabetes prediction model based on GA-XGBoost and stacking ensemble algorithm.
PloS one
Sep 30, 2024
Diabetes, as an incurable lifelong chronic disease, has profound and far-reaching effects on patients. Given this, early intervention is particularly crucial, as it can not only significantly improve the prognosis of patients but also provide valuabl...
Machine learning for post-liver transplant survival: Bridging the gap for long-term outcomes through temporal variation features.
Computer methods and programs in biomedicine
Sep 29, 2024
BACKGROUND: The long-term survival of liver transplant (LT) recipients is essential for optimizing organ allocation and estimating mortality outcomes. While models like the Model-for-End-Stage-Liver-Disease (MELD) predict 90-day mortality on the wait...
Machine learning for anxiety and depression profiling and risk assessment in the aftermath of an emergency.
Artificial intelligence in medicine
Sep 29, 2024
BACKGROUND & OBJECTIVES: Mental health disorders pose an increasing public health challenge worsened by the COVID-19 pandemic. The pandemic highlighted gaps in preparedness, emphasizing the need for early identification of at-risk groups and targeted...
Pain Assessment for Patients with Dementia and Communication Impairment: Feasibility Study of the Usage of Artificial Intelligence-Enabled Wearables.
Sensors (Basel, Switzerland)
Sep 29, 2024
BACKGROUND: Recent studies on machine learning have shown the potential to provide new methods with which to assess pain through the measurement of signals associated with physiologic responses to pain detected by wearables. We conducted a prospectiv...
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