Data_Sheet_1_An Evolutionary Algorithm to Personalize Stool-Based Colorectal Cancer Screening.pdf by Luuk A. van Duuren (12001607)

Flow Φ of the controlled continuous time PDMP. by Benoîte de Saporta (20454662)

“…Tools to assist doctors in treatment decisions and scheduling follow-ups based on patient preferences and medical data would be highly beneficial. These tools should incorporate realistic models of disease progression under treatment, multi-objective optimization of treatment strategies, and efficient algorithms to personalize follow-ups by considering patient history. …”

Fig 4 - by Benoîte de Saporta (20454662)

Practice of patient follow-up. by Benoîte de Saporta (20454662)

Model outputs compared against calibration targets of TB in Viet Nam. by Alvaro Schwalb (8282517)

Comparative performance metrics of ML models. by Rajeev Bopche (20208606)

“…Olavs Hospital in Trondheim, Norway, encompassing 35,591 patients, the framework integrates demographic, laboratory, and comprehensive medical history data to classify patients into high-risk and low-risk BSI groups. …”

Data_Sheet_1_Machine learning prediction of atrial fibrillation in cardiovascular patients using cardiac magnetic resonance and electronic health information.docx by Steven Dykstra (10982971)

“…Seven thousand, six hundred thirty-nine had no prior history of AF and were eligible to train and validate machine learning algorithms. …”

Table 1_Machine learning prediction of post-CABG atrial fibrillation using clinical and pharmacogenomic biomarkers.docx by Lei Hua (465535)

“…Background<p>Postoperative atrial fibrillation (POAF) is a frequent complication following coronary artery bypass grafting (CABG), significantly impacting patient prognosis and healthcare costs. This study aimed to develop an integrated predictive model for POAF risk stratification to optimize clinical management.…”