AIMC Topic: Follow-Up Studies

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Machine Learning Prediction of Early Recurrence in Gastric Cancer: A Nationwide Real-World Study.

Annals of surgical oncology
BACKGROUND: Patients with gastric cancer (GC) who experience early recurrence (ER) within 2 years postoperatively have poor prognoses. This study aimed to analyze and predict ER after curative surgery for patients with GC using machine learning (ML) ...

Predicting macular hole surgery outcomes: Integrating preoperative OCT features with supervised machine learning statistical models.

Indian journal of ophthalmology
PURPOSE: To evaluate various supervised machine learning (ML) statistical models to predict anatomical outcomes after macular hole (MH) surgery using preoperative optical coherence tomography (OCT) features.

Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using machine learning.

European journal of heart failure
AIMS: Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), leading to increased symptom burden and risk of thromboembolism. The HCM-AF score was developed to predict new-onset AF in p...

Comparison of Intratumoral and Peritumoral Deep Learning, Radiomics, and Fusion Models for Predicting KRAS Gene Mutations in Rectal Cancer Based on Endorectal Ultrasound Imaging.

Annals of surgical oncology
MAIN OBJECTIVES: We aimed at comparing intratumoral and peritumoral deep learning, radiomics, and fusion models in predicting KRAS mutations in rectal cancer using endorectal ultrasound imaging.

How to identify patient perception of AI voice robots in the follow-up scenario? A multimodal identity perception method based on deep learning.

Journal of biomedical informatics
OBJECTIVES: Post-discharge follow-up stands as a critical component of post-diagnosis management, and the constraints of healthcare resources impede comprehensive manual follow-up. However, patients are less cooperative with AI follow-up calls or may...

Development and Validation of Machine Learning Model Platelet Index-based Predictor for Colorectal Cancer Stage.

Asian Pacific journal of cancer prevention : APJCP
INTRODUCTION: Colorectal cancer (CRC) staging is essential for effective treatment planning and prognosis. While platelet indices have shown promise in indicating CRC aggressiveness, a platelet index-based predictor for CRC staging has not been estab...

Machine learning algorithms mimicking specialists decision making on initial treatment for people with type 2 diabetes mellitus in Japan diabetes data management study (JDDM76).

Diabetes & metabolic syndrome
OBJECTIVE: To evaluate whether typical machine learning models that mimic specialists' care can successfully reproduce information, not only on whether to prescribe medications but also which hypoglycemic agents to prescribe as initial treatment for ...