Applying Artificial Intelligence to Computational Biology and Medical Informatics
- 1st Edition - September 4, 2026
- Latest edition
- Editor: Mohammad Sufian Badar
- Language: English
Applying Artificial Intelligence to Computational Biology and Medical Informatics explores the transformative role of AI and machine learning in modern biomedical research and he… Read more
Description
Description
Applying Artificial Intelligence to Computational Biology and Medical Informatics explores the transformative role of AI and machine learning in modern biomedical research and healthcare. This volume bridges the gap between computational methods and biological applications, offering a comprehensive introduction for students and researchers across disciplines.
The book covers foundational concepts in AI/ML, computational biology, and medical informatics, followed by in-depth chapters on medical imaging, network biology, chemoinformatics, and public health. It also addresses ethical and societal implications, interpretable AI, and real-world case studies, making complex topics accessible through clear language and structured content.
Designed for early career researchers, students, and professionals without prior expertise in computer science or health sciences, this book provides a progressive learning path from basic to intermediate levels. Readers benefit from practical examples, online resources, and a coherent chapter structure that supports both academic study and applied research.
The book covers foundational concepts in AI/ML, computational biology, and medical informatics, followed by in-depth chapters on medical imaging, network biology, chemoinformatics, and public health. It also addresses ethical and societal implications, interpretable AI, and real-world case studies, making complex topics accessible through clear language and structured content.
Designed for early career researchers, students, and professionals without prior expertise in computer science or health sciences, this book provides a progressive learning path from basic to intermediate levels. Readers benefit from practical examples, online resources, and a coherent chapter structure that supports both academic study and applied research.
Key features
Key features
- Introduces foundational concepts in AI, machine learning, computational biology, and medical informatics, enabling readers from diverse academic backgrounds to build a solid interdisciplinary understanding
- Presents real-world case studies and practical applications of AI/ML in disease diagnosis, treatment, and public health, fostering translational insights and research relevance
- Maintains a coherent pedagogical structure that progresses from basic to intermediate levels, supporting both self-paced learning and integration into academia curricula
Readership
Readership
researchers in bioinformatics, biomedical sciences, computer science, and related interdisciplinary fields
Table of contents
Table of contents
1. Introduction to AI/ML, computational biology, and medical informatics
Mohammad “Sufian” Badar, Ananta Dutta Choudhury, Iqra Khan, Yaqoot Taban Khan, Nabeela Ilyas, Azfar Kamal and Nahed Solouma
2. AI/ML applications in medical imaging
Yukti Sabikhi, Anshika Singh, Sameen Masroor, Chhavi Dudeja, Syed Sibtain Khalid, Aafia Tasneem, Hammad Mansoor, Emad Zeni, Shamim Ahmed Shamim and Mohammad “Sufian” Badar
3. Natural language technologies in biomedical domain
Mohammad “Sufian” Badar, Uzma Khan, Mohd Shadab Alam, Zeenat Mirza, Afzal Ahmad, Khairol Amali bin Ahmad, Ehtesham Jameel, Syed Shad Mohsin, Imran Hussain, Syed Khurram Shahabuddin, Farheen Asaf and Fakhr Ul-Islam
4. AI/ML in chemoinformatics
Mohammad “Sufian” Badar, Taiba Shamim, Mohammed Abaan Kurikkal, Aamir Nehal, Naseem Rao, Fakroul Ridzuan Hashim, Md. Mustafa, Abdus Sattar, Kamran Khan and Zubin Ingah
5. Deep learning methods for network biology
Mohammad “Sufian” Badar, Asma Maheen, Mohammad Rehan Badar, Noora, Aamir Nehal, Abdus Salam Sabir, Sarah Sufian Badar, Syed Zeeshan Hussain and Hamid Omar
6. Probabilistic optimization of ML for heart disease prediction
Aabida Khan, Syed Nazia Shah, Md E.A. Raghib Khan, Yousuf Siddiqui, Belal Bin Asaf, Md. Tabrez Nafis, Asghar Hussain, Ashif Raza and Mohammad “Sufian” Badar
7. The need for interpretable and explainable deep learning data in health care
Mohammad “Sufian” Badar, Md Arshad, Labeebah Rizwan Badar, Jitendra Kumar, Jishnu Anilkumar, Shireen Siddiqui, Omar A. Alamoudi and Hussam Bin Mehare
8. Using hybrid models in healthcare data
Priyanka Mishra and Siddhant Panigrahi
9. Improving disease prediction by integrating multiple ML and optimization techniques
Sara Nadeem, Mohammad Subhan Ali, Syed Ansar Ahmad, Anima Sushim Mathur, Md Zaid Hussain Siddique, Aisha Idris and Mohammad “Sufian” Badar
10. Ethical, societal, and legal issues in AI/ML for healthcare
Mohammad “Sufian” Badar, Huda Shams, Fatemah Rizvi, S.M. Zainul Abedin, Hamid Iqbal, Mohd Asrarul Haque and Aquil Atif
11. Deep learning in gait abnormality detection: Principles and illustrations
Md Arshad, T.N. Giri, Tabindah Hesam, Mohammad Rehan Badar, Ayesha Fatima, Aaliya Sameen and Mohammad “Sufian” Badar
12. Broad applications of network embedding in computational biology, genomics, medicine, and health
Mohammad “Sufian” Badar, Prakriti Singh, Sania Zahid, Sajjad Karim, Muneerah Saeed, Syed Ausaf Ali and Sundus Mohammad Fakhre Alam
13. AI use in clinical prediction
Iqra Khan, Ananta Dutta Choudhury, Iqubal Alam, Mohhamed Salahuddin, Sushim Harish Mathur, Farheen Siddiqui and Mohammad “Sufian” Badar
14. AI/ML for medical informatics and public health
Mohammad “Sufian” Badar, Asma Maheen, Asma Orooj, Shazmeen Shamsi, Syed Fawaz Ayazi, Faiq Alam, Md Kaleem, Mohd Shahzad, Shaista Parveen, Mohd Maksuf Ul Haque and Mohd Afaque
15. AI in medical imaging for developing countries: Challenges and opportunities
Sobia Naaz, Marya Saeed, Rehan Saeed Khan, Akhtar Ali, Azhar Latif, Shabbir Ahmad Warsi, Labeebah Rizwan Badar, Aamna Hassan, Arif Wahab, Abul Kalam Azad and Mohammad “Sufian” Badar
16. AI applications in disease diagnosis and treatment: New applications
Adil Amraz, Nida Iftekhar, Sadaf Fatima, Mohammad Idrees, Mohd Afaque, Shamsheer Alam, Jatin Ahuja, Arslan Mansoor, Danish Reza, Mansaf Alam, Bashir Alam, Syed Zafer Hashmi, Shakeel Ahmad Siddiqui, Aasim Zafar and Hatwib Mugasa
Mohammad “Sufian” Badar, Ananta Dutta Choudhury, Iqra Khan, Yaqoot Taban Khan, Nabeela Ilyas, Azfar Kamal and Nahed Solouma
2. AI/ML applications in medical imaging
Yukti Sabikhi, Anshika Singh, Sameen Masroor, Chhavi Dudeja, Syed Sibtain Khalid, Aafia Tasneem, Hammad Mansoor, Emad Zeni, Shamim Ahmed Shamim and Mohammad “Sufian” Badar
3. Natural language technologies in biomedical domain
Mohammad “Sufian” Badar, Uzma Khan, Mohd Shadab Alam, Zeenat Mirza, Afzal Ahmad, Khairol Amali bin Ahmad, Ehtesham Jameel, Syed Shad Mohsin, Imran Hussain, Syed Khurram Shahabuddin, Farheen Asaf and Fakhr Ul-Islam
4. AI/ML in chemoinformatics
Mohammad “Sufian” Badar, Taiba Shamim, Mohammed Abaan Kurikkal, Aamir Nehal, Naseem Rao, Fakroul Ridzuan Hashim, Md. Mustafa, Abdus Sattar, Kamran Khan and Zubin Ingah
5. Deep learning methods for network biology
Mohammad “Sufian” Badar, Asma Maheen, Mohammad Rehan Badar, Noora, Aamir Nehal, Abdus Salam Sabir, Sarah Sufian Badar, Syed Zeeshan Hussain and Hamid Omar
6. Probabilistic optimization of ML for heart disease prediction
Aabida Khan, Syed Nazia Shah, Md E.A. Raghib Khan, Yousuf Siddiqui, Belal Bin Asaf, Md. Tabrez Nafis, Asghar Hussain, Ashif Raza and Mohammad “Sufian” Badar
7. The need for interpretable and explainable deep learning data in health care
Mohammad “Sufian” Badar, Md Arshad, Labeebah Rizwan Badar, Jitendra Kumar, Jishnu Anilkumar, Shireen Siddiqui, Omar A. Alamoudi and Hussam Bin Mehare
8. Using hybrid models in healthcare data
Priyanka Mishra and Siddhant Panigrahi
9. Improving disease prediction by integrating multiple ML and optimization techniques
Sara Nadeem, Mohammad Subhan Ali, Syed Ansar Ahmad, Anima Sushim Mathur, Md Zaid Hussain Siddique, Aisha Idris and Mohammad “Sufian” Badar
10. Ethical, societal, and legal issues in AI/ML for healthcare
Mohammad “Sufian” Badar, Huda Shams, Fatemah Rizvi, S.M. Zainul Abedin, Hamid Iqbal, Mohd Asrarul Haque and Aquil Atif
11. Deep learning in gait abnormality detection: Principles and illustrations
Md Arshad, T.N. Giri, Tabindah Hesam, Mohammad Rehan Badar, Ayesha Fatima, Aaliya Sameen and Mohammad “Sufian” Badar
12. Broad applications of network embedding in computational biology, genomics, medicine, and health
Mohammad “Sufian” Badar, Prakriti Singh, Sania Zahid, Sajjad Karim, Muneerah Saeed, Syed Ausaf Ali and Sundus Mohammad Fakhre Alam
13. AI use in clinical prediction
Iqra Khan, Ananta Dutta Choudhury, Iqubal Alam, Mohhamed Salahuddin, Sushim Harish Mathur, Farheen Siddiqui and Mohammad “Sufian” Badar
14. AI/ML for medical informatics and public health
Mohammad “Sufian” Badar, Asma Maheen, Asma Orooj, Shazmeen Shamsi, Syed Fawaz Ayazi, Faiq Alam, Md Kaleem, Mohd Shahzad, Shaista Parveen, Mohd Maksuf Ul Haque and Mohd Afaque
15. AI in medical imaging for developing countries: Challenges and opportunities
Sobia Naaz, Marya Saeed, Rehan Saeed Khan, Akhtar Ali, Azhar Latif, Shabbir Ahmad Warsi, Labeebah Rizwan Badar, Aamna Hassan, Arif Wahab, Abul Kalam Azad and Mohammad “Sufian” Badar
16. AI applications in disease diagnosis and treatment: New applications
Adil Amraz, Nida Iftekhar, Sadaf Fatima, Mohammad Idrees, Mohd Afaque, Shamsheer Alam, Jatin Ahuja, Arslan Mansoor, Danish Reza, Mansaf Alam, Bashir Alam, Syed Zafer Hashmi, Shakeel Ahmad Siddiqui, Aasim Zafar and Hatwib Mugasa
Product details
Product details
- Edition: 1
- Latest edition
- Published: September 7, 2026
- Language: English
About the editor
About the editor
MB
Mohammad Sufian Badar
Mohammad Sufian Badar, PhD, is a Professor (temporary) in the Department of Computer Science and Engineering, SEST, Jamia Hamdard, New Delhi, India. Previously, he was Senior Teaching Faculty at UC Riverside, CA, United States, and an Analytics Architect at CenturyLink in Denver, CO, United States. He holds an MS in Molecular Science and Nanotechnology and a PhD in Engineering from Lusiana Tech University. Before that, he earned an MSc. in Bioinformatics from Jamia Millia Islamia, New Delhi. With over 18 years of teaching, research, and industry experience, Dr. Sufian has published in conferences and journals, authored chapters on AI, ML, Blockchain, IoT, Computational Biology, and has six books with Elsevier, Springer, and Bentham. His area of interest is in AI, ML, Computational Biology, and the integration of AI/ML with Health Sciences.
Affiliations and expertise
Senior Teaching Faculty, Department of Bioengineering, University of California, Riverside, CA, USAView book on ScienceDirect
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