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020 _a9783031656408
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024 7 _a10.1007/978-3-031-65640-8
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050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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072 7 _aUYQ
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245 1 0 _aAdvances in Intelligent Disease Diagnosis and Treatment
_h[electronic resource] :
_bResearch Papers in Honour of Prof. Janusz Kacprzyk for Invaluable Contributions /
_cedited by Chee-Peng Lim, Ashlesha Vaidya, Nikhil Jain, Uday Mahorkar, Lakhmi C. Jain.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aX, 304 p. 131 illus., 70 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aIntelligent Systems Reference Library,
_x1868-4408 ;
_v259
505 0 _aRecent advances in Artificial Intelligence in Healthcare -- Pancreatic Cancer Classification Using Multimodal Imaging -- Bayesian optimisation active learning semi supervised classification for an automatic microembolus detection system -- Images Processing and Visualization of Brain Tumors -- 3D Lung Tumor Segmentation System using Adaptive Structure Deep Belief Network -- Optimal deep transfer learning models for stenosis detection in X ray angiography images -- Forward Nonlinear Model for Deep Learning of EEG Auditory Attention Detection in Cocktail Party Problem. Computational Intelligence Based Modelling of Polyneuropathy Diagnosis -- Decentralized Diagnostics The Role of Federated Learning in Modern Medical Imaging -- Boundary Detection of Incomplete Shapes in Breast Thermal Images Using Statistical Shape Modeling -- Enhanced Liver Lesion Detection in Multi Phase CT Images using Unsupervised Domain Adaptation and Feature Generalization -- Decision Support System for Skin Lesion Diagnosis using Deep Learning.
520 _aThe book delves into innovations in AI and related computing paradigms for disease detection and diagnosis. The collected chapters elucidate the use of a variety of AI and related methodologies to address specific medical challenges. From detecting pancreatic cancer, classifying micro-emboli in stroke diagnosis, to segmenting brain tumours from MRI data, and more, the culmination of these studies underscores the transformative impact AI and digital technologies can have on healthcare, emphasising their potential to enhance medical treatment and improve patient care.
650 0 _aComputational intelligence.
_964052
650 0 _aBiomedical engineering.
650 0 _aArtificial intelligence.
_958441
650 0 _aMedical informatics.
_960693
650 1 4 _aComputational Intelligence.
_964052
650 2 4 _aBiomedical Engineering and Bioengineering.
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aHealth Informatics.
700 1 _aLim, Chee-Peng.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
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700 1 _aVaidya, Ashlesha.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_984479
700 1 _aJain, Nikhil.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_984480
700 1 _aMahorkar, Uday.
_eeditor.
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_984481
700 1 _aJain, Lakhmi C.
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_979431
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783031656422
830 0 _aIntelligent Systems Reference Library,
_x1868-4408 ;
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_967034
856 4 0 _uhttps://doi.org/10.1007/978-3-031-65640-8
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