Medical AI models need more context to prepare for the clinic: Challenges and potential solutions

Medical artificial intelligence is a hugely appealing concept. In theory, models can analyze vast amounts of information, recognize subtle patterns in data, and are never too tired or busy to provide ...

Using data to reduce subjectivity in landslide susceptibility mapping

In recent years, numerous landslides on hillsides in urban and rural areas have underscored that understanding and predicting ...
IEEE

A Hybrid Quantum-Classical Approach for Multi-Class Skin Disease Classification Using a 4-Qubit Model

Abstract: Quantum machine learning (QML) presents a promising avenue for addressing complex classification challenges, yet its application in medical imaging remains largely unexplored. This work ...
IEEE

Cancer Cell Classification From Peripheral Blood Smear Data Using the YOLOv8 Architecture

Abstract: The accurate classification of cancer cells in the peripheral blood is essential for the diagnosis of leukemia and has traditionally been carried out by analyzing laboratory images. In this ...
Psychiatry Advisor

Accuracy of Machine Learning in Predicting CVD Risk in Bipolar Disease

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...