Artificial Intelligence (AI), which embraces machine learning, deep learning and cognitive computing, makes computers able to learn from experience and to adjust to new inputs by mimicking “cognitive” tasks such as reasoning, learning, problem solving, and several others that are usually associated with the human mind. Thanks to AI-based algorithms, computers can be trained to accomplish a high variety of tasks by processing large amounts of data through the recognition of specific patterns. Nowadays, the use of AI is becoming more and more popular in all disciplines. Medicine, physiology, and even surgery, are fields which are deeply affected even though they have raised several ethical issues. Human physiology seeks to understand the mechanisms that work to keep the human body healthy and functioning, focusing on how different systems (like the nervous, cardiocirculatory system, respiratory, endocrine system or immune system), organs, cells, and biomolecules carry out different chemical and physical functions. Traditionally, studies on human physiology are conducted in laboratories where experiments often require the imposition of repeated influences on an organic system. Recently, AI has been proposed as a tool to support problem solving in human physiology, possibly allowing a reduction in the number of invasive experiments, as well as predicting pathologic processes that are not detected through standard testing. AI utility in human physiology is, however, still to be demonstrated.
The Guest Editors of this Research Topic welcome original research articles and/or reviews on the role of AI in physiology which aim to:
- Assess the key role of AI in the interpretation, prediction and management of both physiologic and pathologic processes encountered in medicine and surgery.
- Understand the feasibility of AI as an additional or complementary tool to the traditional diagnostic tests.
- Hypothesize a place for AI as an instrument to predict risk of physiologic derangement or postoperative morbidity.
Specific topics include, but are not limited, to the following areas:
• Machine learning and deep learning in human physiology;
• Knowledge engineering in human physiology;
• AI application for exercise physiology, pre- and postoperative diagnostic, neuro, cardiac pulmonary and hematologic physiology;
• AI for drug development, utilization and safety pharmacology;
• AI-based models for physiological systems;
• Ethics of AI in human physiology.
Artificial Intelligence (AI), which embraces machine learning, deep learning and cognitive computing, makes computers able to learn from experience and to adjust to new inputs by mimicking “cognitive” tasks such as reasoning, learning, problem solving, and several others that are usually associated with the human mind. Thanks to AI-based algorithms, computers can be trained to accomplish a high variety of tasks by processing large amounts of data through the recognition of specific patterns. Nowadays, the use of AI is becoming more and more popular in all disciplines. Medicine, physiology, and even surgery, are fields which are deeply affected even though they have raised several ethical issues. Human physiology seeks to understand the mechanisms that work to keep the human body healthy and functioning, focusing on how different systems (like the nervous, cardiocirculatory system, respiratory, endocrine system or immune system), organs, cells, and biomolecules carry out different chemical and physical functions. Traditionally, studies on human physiology are conducted in laboratories where experiments often require the imposition of repeated influences on an organic system. Recently, AI has been proposed as a tool to support problem solving in human physiology, possibly allowing a reduction in the number of invasive experiments, as well as predicting pathologic processes that are not detected through standard testing. AI utility in human physiology is, however, still to be demonstrated.
The Guest Editors of this Research Topic welcome original research articles and/or reviews on the role of AI in physiology which aim to:
- Assess the key role of AI in the interpretation, prediction and management of both physiologic and pathologic processes encountered in medicine and surgery.
- Understand the feasibility of AI as an additional or complementary tool to the traditional diagnostic tests.
- Hypothesize a place for AI as an instrument to predict risk of physiologic derangement or postoperative morbidity.
Specific topics include, but are not limited, to the following areas:
• Machine learning and deep learning in human physiology;
• Knowledge engineering in human physiology;
• AI application for exercise physiology, pre- and postoperative diagnostic, neuro, cardiac pulmonary and hematologic physiology;
• AI for drug development, utilization and safety pharmacology;
• AI-based models for physiological systems;
• Ethics of AI in human physiology.
