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Machine Learning in Forensic Evidence Examination discusses methodologies for the application of machine learning to the field of forensic science.
List of contents
1. Basic Introduction to Machine Learning and its Approaches in Forensic Application 2. Potential Application of Machine Learning in Forensic Trace Evidence Examination 3. Potential Application of Machine Learning in Forensic Questioned Document Examination 4. Application of Machine Learning in the Field of Forensic Medicine 5. Application of Machine Learning in the Field of Forensic Biology and Serological Evidence Identification 6. A Machine Learning Approach for the Identification of Toxicological Evidence 7. Application of Machine Learning in the Field of Forensic Fingerprint Sciences 8. A Machine Learning Approach for the Digital Forensics 9. Potential Application of Machine Learning in Forensic Odontology 10. Potential Application of Machine Learning in Forensic Anthropology 11. Potential Application of Machine Learning in Forensic Ballistics 12. Application of Machine Learning in Big Data Analysis
About the author
Niha Ansari is Assistant Professor at the National Forensic Science University in Gandhinagar. She earned her Ph.D. in Forensic Science from Gujarat University, where she conducted the pioneering research 'Study on Changes in Vitreous Humours concerning Time since Death', utilising nano sensor smartphone applications and microfluidic devices. Dr Ansari has also held positions at Jain University in Bangalore. She has published a number of chapters in edited volumes, and 14 articles in peer-reviewed international journal publications. Her research interests encompass forensic nanotechnology, microfluidics, and smartphone-based sensors. She has participated in numerous conferences, workshops, and training sessions, imparting knowledge and skills to professionals and students alike. Among her accolades, Dr Ansari has been awarded the Maulana Azad National Fellowship by the University Grant Commission and the Best PhD Thesis Award by CHARUSAT. She is a part of the Editorial board of The Science publishing group.
