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Research: Prof. Davide La Torre explores AI applications for medicine
Artificial Intelligence (AI) and Machine Learning (ML) are reshaping the landscape of medicine, offering substantial potential for advancements in disease diagnosis and treatment. Davide La Torre, a distinguished international scholar and full professor of applied mathematics and artificial intelligence at SKEMA Business School, has recently collaborated with five other leading scientists to co-author a book titled "Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications."
Davide La Torre has examined the impacts of AI in medicine in a book released in March 2024. "This book introduces readers to the methodology and algorithms of AI/ML as well as to cutting-edge applications in medicine, such as cancer, precision medicine, critical care, personalised medicine, telemedicine, drug discovery, molecular characterisation, and the mental health of patients," explains Davide La Torre.
A Giant leap for medicine?
The impact of AI in medicine is immense. For several months, there have been notable advances in how diseases are diagnosed, treated, and managed. La Torre's book explores these advances in detail, highlighting how AI can assist in creating tailored treatments for patients, thus significantly improving health outcomes. Furthermore, the book addresses the ethical challenges posed by the use of AI in medicine, a growing concern among healthcare professionals. "Medicine research and personalised clinical treatments are rapidly transformed by artificial intelligence and machine learning. The content of the publication is tailored to the reader's needs in terms of type and fundamentals. It covers the current ethical issues and potential developments in this field."
This work is an invaluable resource not only for academics and IT industry professionals but also for educators, students, and anyone involved in the use and development of AI in the medical field. It paves the way for a new era of medicine.
Latest publications by Davide La Torre:
[1] Reinforcement learning applications in environmental sustainability: a review (2024). Artificial Intelligence Review, 57(88), pp. 1-68.
[4] Co-evolution of Neural Architectures and Features for Stock Market Forecasting: A Multi-objective Decision Perspective (2023). Decision Support Systems, 174, pp. 114015.
[6] Team Formation for Human-Artificial Intelligence Collaboration in the Workplace: A Goal Programming Model to Foster Organizational Change (2023). IEEE Transactions on Engineering Management, 70(5), pp. 1966-1976.
