Predictive analytics in healthcare. Volume 1, Transforming the future of medicine /
Transforming the future of medicine.
edited by Vinithasree Subbhuraam.
- 1 online resource (various pagings) : illustrations (some color).
- [IOP release $release] IOP ebooks. [2021 collection] IPEM-IOP series in physics and engineering in medicine and biology .
- IOP (Series). Release 21. IPEM-IOP series in physics and engineering in medicine and biology. IOP ebooks. 2021 collection. .
"Version: 202112"--Title page verso.
Includes bibliographical references.
1. Predictive analytics in healthcare / Vinithasree Subbhuraam -- 2. Predictive analytics in public health surveillance / Vinithasree Subbhuraam and Islamiyyat Olatinwo -- 3. FemTech solutions for advancing women's health / Vinithasree Subbhuraam -- 4. Telemedicine / Vinithasree Subbhuraam and Debabrata Panigrahi -- 5. Pervasive healthcare applications in neurology / Vinithasree Subbhuraam and Dyuti Kumar -- 6. Extraction of fetal head section from ultrasound images using a soft-computing based image mining system--a study with Kapur's thresholding and segmentation / V. Rajinikanth and Seifedine Kadry -- 7. Classification of retinal fundus images into healthy/AMD classes using mayfly algorithm selected features / David Taniar, Seifedine Kadry and Venkatesan Rajinikanth.
Healthcare delivery is progressing into a format wherein analysis of a combination of disease data and patient data using predictive analytics provides additional information for physicians and healthcare providers to make more accurate detection, diagnosis, and treatment decisions. This is a unique book offering a novel course on Predictive Analytics in Healthcare.
Medical Students, Physicians, Biomedical Engineers, Data Scientists, Hospital Administrators.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
Dr. Vinithasree Subbhuraam has over 15 years of experience in biomedical data science and has utilized predictive analytics for designing clinical decision support systems to detect diseases such as carotid atherosclerosis, fatty liver, diabetes, epilepsy, and cancers in the thyroid, breast, ovaries, and prostate. She has MS and PhD degrees in Biomedical Engineering from Nanyang Technological University, Singapore, and a Bachelor's degree in Electronics and Communication Engineering from PSG College of Technology, Coimbatore, India.
9780750323123 9780750323116
10.1088/978-0-7503-2312-3 doi
Medical informatics.
Medicine--Data processing.
Predictive analytics.
Medical Informatics.
Data Science.
Forecasting.
Biomedical engineering.
Biomedical engineering.
R858 / .P743 2021eb
610.285
W 26.5 / P923 2021eb
"Version: 202112"--Title page verso.
Includes bibliographical references.
1. Predictive analytics in healthcare / Vinithasree Subbhuraam -- 2. Predictive analytics in public health surveillance / Vinithasree Subbhuraam and Islamiyyat Olatinwo -- 3. FemTech solutions for advancing women's health / Vinithasree Subbhuraam -- 4. Telemedicine / Vinithasree Subbhuraam and Debabrata Panigrahi -- 5. Pervasive healthcare applications in neurology / Vinithasree Subbhuraam and Dyuti Kumar -- 6. Extraction of fetal head section from ultrasound images using a soft-computing based image mining system--a study with Kapur's thresholding and segmentation / V. Rajinikanth and Seifedine Kadry -- 7. Classification of retinal fundus images into healthy/AMD classes using mayfly algorithm selected features / David Taniar, Seifedine Kadry and Venkatesan Rajinikanth.
Healthcare delivery is progressing into a format wherein analysis of a combination of disease data and patient data using predictive analytics provides additional information for physicians and healthcare providers to make more accurate detection, diagnosis, and treatment decisions. This is a unique book offering a novel course on Predictive Analytics in Healthcare.
Medical Students, Physicians, Biomedical Engineers, Data Scientists, Hospital Administrators.
Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
Dr. Vinithasree Subbhuraam has over 15 years of experience in biomedical data science and has utilized predictive analytics for designing clinical decision support systems to detect diseases such as carotid atherosclerosis, fatty liver, diabetes, epilepsy, and cancers in the thyroid, breast, ovaries, and prostate. She has MS and PhD degrees in Biomedical Engineering from Nanyang Technological University, Singapore, and a Bachelor's degree in Electronics and Communication Engineering from PSG College of Technology, Coimbatore, India.
9780750323123 9780750323116
10.1088/978-0-7503-2312-3 doi
Medical informatics.
Medicine--Data processing.
Predictive analytics.
Medical Informatics.
Data Science.
Forecasting.
Biomedical engineering.
Biomedical engineering.
R858 / .P743 2021eb
610.285
W 26.5 / P923 2021eb