AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Follow-Up Studies

Showing 271 to 280 of 723 articles

Clear Filters

Diabetic Retinopathy Screening with Automated Retinal Image Analysis in a Primary Care Setting Improves Adherence to Ophthalmic Care.

Ophthalmology. Retina
PURPOSE: Retinal screening examinations can prevent vision loss resulting from diabetes but are costly and highly underused. We hypothesized that artificial intelligence-assisted nonmydriatic point-of-care screening administered during primary care v...

Improving blood glucose level predictability using machine learning.

Diabetes/metabolism research and reviews
This study was designed to improve blood glucose level predictability and future hypoglycemic and hyperglycemic event alerts through a novel patient-specific supervised-machine-learning (SML) analysis of glucose level based on a continuous-glucose-mo...

Predicting individual improvement in schizophrenia symptom severity at 1-year follow-up: Comparison of connectomic, structural, and clinical predictors.

Human brain mapping
In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at bas...

A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy.

Breast cancer research : BCR
BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and va...

Artificial Intelligence-Assisted System in Postoperative Follow-up of Orthopedic Patients: Exploratory Quantitative and Qualitative Study.

Journal of medical Internet research
BACKGROUND: Patient follow-up is an essential part of hospital ward management. With the development of deep learning algorithms, individual follow-up assignments might be completed by artificial intelligence (AI). We developed an AI-assisted follow-...

Predicting Survival After Extracorporeal Membrane Oxygenation by Using Machine Learning.

The Annals of thoracic surgery
BACKGROUND: Venoarterial (VA) extracorporeal membrane oxygenation (ECMO) undoubtedly saves many lives, but it is associated with a high degree of patient morbidity, mortality, and resource use. This study aimed to develop a machine learning algorithm...

Stability Assessment of Intracranial Aneurysms Using Machine Learning Based on Clinical and Morphological Features.

Translational stroke research
Machine learning (ML) as a novel approach could help clinicians address the challenge of accurate stability assessment of unruptured intracranial aneurysms (IAs). We developed multiple ML models for IA stability assessment and compare their performan...

Artificial intelligence for early prediction of pulmonary hypertension using electrocardiography.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
BACKGROUND: Screening and early diagnosis of pulmonary hypertension (PH) are critical for managing progression and preventing associated mortality; however, there are no tools for this purpose. We developed and validated an artificial intelligence (A...