Predicting how cancer patients will respond to treatment remains a critical challenge. Immune checkpoint inhibitors (ICIs), a ...

Advanced Machine Learning Models for Gender-Specific Antidepressant Response Prediction: Overcoming Data Imbalance for Precision Psychiatry Depressive disorders are complex, multifactorial conditions ...

Development of Prediction Model for Brain Amyloid-Beta Accumulation for Early Screening of Alzheimer's Disease MACHINE LEARNING MODEL USING ...

The AUC-PRC values of the fullPIERS model remained low (0.2 to 0.4), indicating low ... Several authors have an intellectual ...

An AI tool appeared superior to two FDA-approved biomarkers for predicting how people with cancer will respond to immune ...

Current clinical tools rely on known cardiovascular risk elements, but they often do not account for complex interactions between multiple variables. Machine learning, with its ability to process vast ...

AI, when properly implemented, has the power to transform emergency medicine by enhancing patient outcomes, reducing ...

To develop a machine learning (ML) algorithm to predict survival probabilities for patients with epithelial ovarian cancer (EOC).Data were obtained from the SEER database for women diagnosed with EOC ...

Students should not approach other offices within The American University in Cairo (AUC) for funding without prior communication with the Undergraduate Research Program. If extra funding is found ...

A large number of students from Egypt and from more than 30 other countries normally attend AUC’s summer session. While the majority are pursuing degrees at AUC during the academic year, many students ...

To identify such biomarkers, initially LASSO in association with four machine learning models such as Random Forest (RF), Support Vector Machine ... Experimental results suggest that our proposed ...

Objectives: This study aimed to discover plasma proteins indicative of stroke severity in patients with acute ischemic stroke (AIS) using aptamer-based proteomics and supervised machine learning ...