As a subfield of machine learning, reinforcement learning (RL) aims at optimizing decision
making by using interaction samples of an agent with its environment and the potentially …

Discovering new treatments and personalizing existing ones is one of the major goals of
modern clinical research. In the last decade, Artificial Intelligence (AI) has enabled the …

Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …

In this paper, we present a new fractional-order mathematical model for a tumor-immune
surveillance mechanism. We analyze the interactions between various tumor cell …

Artificial intelligence in health care has experienced remarkable innovation and progress in
the last decade. Significant advancements can be attributed to the utilization of artificial …

An optimal antimicrobial dose provides enough drug to achieve a clinical response while
minimizing toxicity and development of drug resistance. There can be considerable …

The explosive growth in medical devices, imaging and diagnostics, computing, and
communication and information technologies in drug development and healthcare has …

Machine learning (ML) has the potential to transform oncology and, more broadly, medicine.
1 The introduction of ML in health care has been enabled by the digitization of patient data …

The data-driven identification of disease states and treatment options is a crucial challenge
for precision oncology. Artificial intelligence (AI) offers unique opportunities for enhancing …

Background and objective Cancer is one of the major causes of death worldwide and
chemotherapies are the most significant anti-cancer therapy, in spite of the emerging …