2022 International Mobile and Embedded Technology Conference (MECON) · 2022 · 25 citations · 18 references
ComputingComputer ScienceHealth InformaticsBiomedical ImagingDiagnostic ImagingMachine LearningComputer-aided DiagnosisDeep LearningMedical Image AnalysisMedical ImagingPattern RecognitionRepresentation LearningAccuracyDeep Learning-based ClassificationDeep Learning-based DetectionDeep Learning-based DiagnosisMachine Learning For Healthcare
Deep learning (DL) is the technique encouraging clinical staff and physicians to work on a variety of data using DL algorithms. DL techniques have given a rise in the medical facilities with better accuracy and early detection of disease. These techniques in medical imaging are one of the most trending topics among the researchers across the globe. To perceive the advantages and disadvantages of the recent techniques in medical science, several researchers have discussed techniques for classification, detection and segmentation of the medical data. Medical data is of two types, one is the electronic data and second, manual data collected from surveys and clinics. This paper gives insight into DL techniques in healthcare along with their merits and demerits. Further, a description of the most significant datasets in healthcare has been given. It also gives a brief of various challenges faced by the researchers to implement new techniques.
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NiftyNet: a deep-learning platform for medical imaging
Eli Gibson, Carole H. Sudre, Lucas Fidon et al. · Computer Methods and Programs in Biomedicine · 2018 · 557 citations · Full text
Understanding adversarial attacks on deep learning based medical image analysis systems
Xingjun Ma, Yuhao Niu, Lin Gu et al. · Pattern Recognition · 2020 · 530 citations · Full text
Medical image classification using synergic deep learning
Jianpeng Zhang, Yutong Xie, Qi Wu et al. · Medical Image Analysis · 2019 · 394 citations
A call for deep-learning healthcare
Beau Norgeot, Benjamin S. Glicksberg, Atul J. Butte · Nature Medicine · 2018 · 260 citations