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Prospective Studies

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A deep-learning system integrating electrocardiograms and laboratory indicators for diagnosing acute aortic dissection and acute myocardial infarction.

International journal of cardiology
BACKGROUND: Acute Stanford Type A aortic dissection (AAD-type A) and acute myocardial infarction (AMI) present with similar symptoms but require distinct treatments. Efficient differentiation is critical due to limited access to radiological equipmen...

Waveform characteristics in thoracic paravertebral space: a prospective observational study.

F1000Research
BACKGROUND: With increased use of thoracic paravertebral block (TPVB) in thoracic surgery, many faced the challenge of locating the thoracic paravertebral space (TPVS) ultrasonographically. This observational study aimed to investigate the waveform c...

Machine Learning to Predict Mortality in Older Patients With Cancer: Development and External Validation of the Geriatric Cancer Scoring System Using Two Large French Cohorts.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: Establishing an accurate prognosis remains challenging in older patients with cancer because of the population's heterogeneity and the current predictive models' reduced ability to capture the complex interactions between oncologic and geria...

Machine learning-based algorithm of drug-resistant prediction in newly diagnosed patients with temporal lobe epilepsy.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVES: To develop a predicted algorithm for drug-resistant epilepsy (DRE) in newly diagnosed temporal lobe epilepsy (TLE) patients.

The association of lifestyle with cardiovascular and all-cause mortality based on machine learning: a prospective study from the NHANES.

BMC public health
BACKGROUND: Lifestyle and cardiovascular mortality and all-cause mortality have been exhaustively explored by traditional methods, but the advantages of machine learning (ML) over traditional methods may lead to different or more precise conclusions....

Machine learning model to predict the adherence of tuberculosis patients experiencing increased levels of liver enzymes in Indonesia.

PloS one
Indonesia is still the second-highest tuberculosis burden country in the world. The antituberculosis adverse drug reaction and adherence may influence the success of treatment. The objective of this study is to define the model for predicting the adh...

Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India: Protocol for a Prospective Cohort Study.

JMIR research protocols
BACKGROUND: Type 2 diabetes (T2D) is a leading cause of premature morbidity and mortality globally and affects more than 100 million people in the world's most populous country, India. Nutrition is a critical and evidence-based component of effective...

The role of CTGF and MFG-E8 in the prognosis assessment of SCAP: a study combining machine learning and nomogram analysis.

Frontiers in immunology
BACKGROUND: Severe Community-Acquired Pneumonia (SCAP) is a serious global health issue with high incidence and mortality rates. In recent years, the role of biomarkers such as Connective Tissue Growth Factor (CTGF) and Milk Fat Globule-Epidermal Gro...

Diagnostic Performance of Different Examination Types and Learning Curves of Radiologists for 5G-Based Robot-Assisted Tele-Ultrasonography: A Prospective and Large-Scale Study.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVE: To investigate the feasibility of remotely providing routine ultrasound (US) examinations to patients using a fifth-generation-based robot-assisted tele-ultrasonography (RATU) system in a real-world setting.