From Algorithms to Ailments
Editat de Madhu Chetty, Jennifer Hallinanen Limba Engleză Hardback – 16 iul 2026
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Specificații
ISBN-10: 303211022X
Pagini: 240
Ilustrații: Approx. 200 p.
Dimensiuni: 160 x 241 x 19 mm
Greutate: 0.48 kg
Editura: Springer
Notă biografică
Dr Madhu Chetty, as an academic at Federation University Australia, serves as Professor in Information Technology within the Institute of Innovation, Science and Sustainability (IISS), and as the Director of AI and ML Stream within Health Innovation and Transformation Centre (HITC). He has over 40 years of tertiary teaching, research, and leadership experience within Australia and overseas. He has a prolific publication record, several visiting appointments at various international universities, and has supervised over 25 doctoral students. He has been recipient of several grants and awards including Australia-India Strategic Research Fund, award for excellence in research supervision, and commendation for community engagement. He has served as general chair of IEEE international conferences, vice chair of the IEEE Victorian/Tasmanian Section, deputy head of school at Monash University Australia, and editorial board member of high impact journals.
Dr Jennifer Hallinan has degrees in both molecular biology and computer science, and combined these into a PhD in computational biology. She has researched and taught at Universities in both Australia and the United Kingdom, working on bioinformatics and synthetic biology and worked at Harvard Medical School on biological network analysis. She has authored over 60 papers published in peer-reviewed journals, and supervised over 20 PhD and Masters students. She was an advisor for three iGEM teams at Newcastle University, UK, all of which won gold medals. She is active in the IEEE, being Program Chair for the 2021 International Conference on Bioinformatics and Computational Biology, and serves as Vice-Chair for Education and Outreach of the IEEE Computational Intelligence Society.
Cuprins
Chapter 1. From Data Science to Artificial Intelligence.- Chapter 2. Molecular Biology Lite.- Chapter 3. Application of Deep Learning to Healthcare.- Chapter 4. Computational modeling paradigms in systems biology.- Chapter 5. Image Analysis and Cancer Detection.- Chapter 6. Genomics and Synthetic Biology.- Chapter 7. Drug Discovery and Drug Repurposing.- Epilogue (about 7-10 pages long).