LEADER 03791nam 22005895 450 001 9910522913203321 005 20230313191706.0 010 $a3-030-76732-9 024 7 $a10.1007/978-3-030-76732-7 035 $a(CKB)4100000011982005 035 $a(MiAaPQ)EBC6678864 035 $a(Au-PeEL)EBL6678864 035 $a(DE-He213)978-3-030-76732-7 035 $a(PPN)258061006 035 $a(EXLCZ)994100000011982005 100 $a20210714d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aTracking and Preventing Diseases with Artificial Intelligence /$fedited by Mayuri Mehta, Philippe Fournier-Viger, Maulika Patel, Jerry Chun-Wei Lin 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (266 pages) 225 1 $aIntelligent Systems Reference Library,$x1868-4408 ;$v206 311 $a3-030-76731-0 320 $aIncludes bibliographical references. 327 $aStress Identification from Speech using Clustering techniques -- Comparative Study and Detection of COVID-19 and Related Viral Pneumonia using a Fine-tuned Deep Transfer Learning -- Predicting Glaucoma Diagnosis using AI -- Diagnosis and Analysis of Tuberculosis Disease using Simple Neural Network and Deep Learning Approach for Chest X-ray Images -- Adaptive Machine Learning Algorithm and Analytics of Big Genomic Data for Gene Prediction. 330 $aThis book presents an overview of how machine learning and data mining techniques are used for tracking and preventing diseases. It covers several aspects such as stress level identification of a person from his/her speech, automatic diagnosis of disease from X-ray images, intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells, information retrieval from electronic medical record using named entity recognition approaches, and prediction of drug-target interactions. The book is suitable for computer scientists having a bachelor degree in computer science. The book is an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care. Researchers working in the multidisciplinary areas use this book to discover the current developments. Besides its use in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases. Medical institutions use this book as reference material and give tutorials to medical experts on how the advanced AI and ML techniques contribute to the diagnosis and prediction of the diseases. 410 0$aIntelligent Systems Reference Library,$x1868-4408 ;$v206 606 $aComputational intelligence 606 $aBiomedical engineering 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aBiomedical Engineering and Bioengineering 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aBiomedical engineering. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aBiomedical Engineering and Bioengineering. 615 24$aArtificial Intelligence. 676 $a610.285 702 $aMehta$b Mayuri 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910522913203321 996 $aTracking and preventing diseases with artificial intelligence$92820439 997 $aUNINA