Computational Methods in Psychiatry

Erscheinungsjahr 2024
ISBN: 978-981-99-6639-4
Verlag: Springer

Buch, Englisch, 348 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 605 g

This book presents a particular area of interest in computing psychiatry with the modelling of mood and anxiety disorders. It highlights various methods for building these models. Clinical applications are prevalent due to the growth and interaction of these multiple approaches. Besides, it outlines some original predictive and computational modelling ideas for enhancing psychological treatment interventions.

Computational psychiatry combines multiple levels and types of computation with different data types to improve mental illness understanding, prediction, and treatment.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Battineni, Gopi

Mittal, Mamta

Chintalapudi, Nalini

Fachgebiete

• Sozialwissenschaften Psychologie Psychologie / Allgemeines & Theorie Psychologische Forschungsmethoden
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Psychiatrie, Sozialpsychiatrie, Suchttherapie
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Neurowissenschaften, Kognitionswissenschaft
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft
• Sozialwissenschaften Psychologie Psychotherapie / Klinische Psychologie

Inhaltsverzeichnis

1 COVID impact on Italian health system: from self determination to solidarity.- 2 Mental health and psychological wellbeing of maritime personnel: Factors affecting Mental Health of Seafarers on Board Merchant Ships.- 3 Intelligent monitoring system based on ATMEGA microcontrollers in healthcare with stress reduce effect.- 4 Predictive Measures to tackle Mental Health During COVID-19.- 5 Intelligent Digital Monitoring of levels of stress.- 6 Consequences of brain health in digital era.- 7 AI-based Framework for Association between Depression and Physical Health Disorders.- 8 WFH and its impacts on lifestyle of humanoid in the context of covid-19.- 9 Digital Mental Health Prediction and Enhancement using Deep Feed Forward Neural Network and Psychiatry Tools.- 10 The challenge of self-diagnosis on mental health through social media: A qualitative study.- 11 Relationship between mortality and mental health disorders.- 12 Recent Developments in the Application of Computer-Aided DrugDesign to Neurodegenerative Disorders.- 13 Intelligent Stress Cause and its Level Monitoring of Teachers in Private Engineering Colleges.- 14 Student Stress Detection in Online Learning during Outbreak.- 15 A Review on Mental and Physical Health Acceptance of Immunization and Vaccination for COVID-19 Pandemic a Conscience of Humans Perception Using SWOT Analysis.- 16 Application of Smart Intelligent technologies in health care using 4.0 Perspectives.

Über Autor(innen)

Dr Gopi Battineni is a research associate at the Clinical research centre, School of Medicinal and Health Products Sciences, University of Camerino, Italy since 2022. A master’s degree (with honours) in Computer Science and Engineering from Sheffield Hallam University, UK in 2016; and a master’s degree (with honours) in Enterprise Engineering from the University of Bordeaux, France in 2018, and a PhD in One health at the University of Camerino in 2021 with award of excellent cum lode. His research area includes telemedicine, process mining, natural language processing, data mining, big data, and machine learning. Dr Battineni is a member of the European Research Committee and has published more than 90 research papers in SCI, SCIE and Scopus-indexed journals and attending conferences, seminars, and guest talks on an international platform. He is a reviewer of many reputed international journals from different popular publishing houses such as Elsevier, MDPI, Wiley, Dove, plus one, BMJ etc. He managed and chaired different international conferences. He is an Associate Editor with reputed SCIE Indexed journals: Journal of Personalized Medicine and Algorithms (MDPI, Switzerland). Dr Mamta Mittal is working as Head and Associate Professor (Data Analytics and Data Science) at Delhi Skill & Entrepreneurship University (under the Government of NCT Delhi), New Delhi. She received PhD in Computer Science and Engineering from Thapar University, Patiala. She has been teaching for the last 18+ years with an emphasis on Data Mining, Machine Learning, DBMS, and Data Structure. Dr Mittal is a Lifetime member of CSI and published and communicated more than 90 research papers in SCI, SCIE, and Scopus indexed Journals. She holds five patents and two copyrights in Artificial Intelligence, IoT, and Deep Learning. Dr Mittal has edited/authored many books with reputed publishers like Springer, IOS Press, Elsevier, and CRC Press and working on DST approved Project “Development of IoT-based hybrid navigation module for mid-sized autonomous vehicles” with a research grant of 25 Lakhs. Currently, she is guiding PhD scholars in Machine Learning, Computer Vision, and Deep Learning. She is the book Series editor of Health Informatics & Healthcare: using AI & Smart Computing & another Series Edge AI in Future Computing with CRC Press, Taylor & Francis, USA. Dr Mittal is an Editorial Board member with InterScience, Bentham Science, Springer, and Elsevier and has Chaired several Conferences. She is Associate Editor with reputed SCIE Indexed journals: Earth Information Science (Springer) and Dyna (Spain). Dr Nalini Chintalapudi is a researcher at the clinical research centre, School of Medicinal and Health Products Sciences, University of Camerino in Italy. She earned a degree (with first-class distinction) in Computer Science at Jawaharlal Nehru Technological University, India; a master’s degree (with honours) in Computer Science and Engineering from the same university in 2015. She completed PhD in Computer Science and Mathematics at the University of Camerino. Her research area includes Text mining, Natural Language Processing, Data mining, big data and Machine learning. Dr Nalini Chintalapudi is a member of the European Research Committee and has published more than 45 research papers in SCI, SCIE and Scopus-indexed journals.