Medical Imaging
Deep learning for reading and interpreting medical images, such as ultrasound, to support diagnosis and clinical decisions.
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Ablation of the dystrophin Dp71f alternative C-terminal variant increases sarcoma tumour cell aggressiveness
N Alnassar, J Hajto, RMH Rumney, S Verma, M Borczyk, C Saha, et al. Cited by 7
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Advancing COVID-19 poverty estimation with satellite imagery-based deep learning techniques: a systematic review
S Mishra, SK Satapathy, SB Cho, SN Mohanty, S Sah, S Sharma. Cited by 6
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LLM2FEA: Discover novel designs with generative evolutionary multitasking
M Wong, J Liu, T Rios, S Menzel, YS Ong. Cited by 7
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SeRTS: Self-rewarding tree search for biomedical retrieval-augmented generation
M Hu, L Zong, H Wang, J Zhou, J Li, Y Gao, KF Wong, Y Li, I King. Cited by 10
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T-Fusion Net: A Novel Deep Neural Network Augmented with Multiple Localizations Based Spatial Attention Mechanisms for Covid-19 Detection
S Ghosh, A Chatterjee. Cited by 11
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Mechanism-aware and multimodal AI: beyond model-agnostic interpretation
A Occhipinti, S Verma, C Angione. Cited by 24
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Mome: Mixture of multimodal experts for cancer survival prediction
C Xiong, H Chen, H Zheng, D Wei, Y Zheng, JJY Sung, I King. Cited by 36
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Finding Sets of Pareto Sets in Real-World Scenarios – A Multitask Multiobjective Perspective
J Liu, YS Ong, M Wong. Cited by 3
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Improving Cognitive Safety in High-Risk Patients: A Cognitive Assessment-based Approach
M Chignell, A Iglar, M Singh, M Furlano, TNT Hall, JB Morton, JS Lee
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Melioidosis in Patients with COVID-19 Exposed to Contaminated Tap Water, Thailand, 2021
P Tantirat, Y Chantarawichian, P Taweewigyakarn, S Kripattanapong, C Jitpeera, P Doungngern, C Phiancharoen, R Tangwangvivat, S Hinjoy, A Sujariyakul, P Amornchai, G Wongsuvan, V Hantakun, V Wuthiekanun, J Thaipadungpanit, NR Thomson, DAB Dance, C Chewapreecha, EM Batty, D…. Cited by 9
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Uncovering potential diagnostic and pathophysiological roles of α‐synuclein and DJ ‐1 in melanoma
A Quesnel, LD Martin, C Tarzi, VPE Lenis, NP Coles, M Islam, C Angione, TF Outeiro, AA Khundakar, PS Filippou. Cited by 9
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Agglomeration Rate Estimation of Mineral Oil based ZnO Nanofluids by Dielectric Spectroscopy
S Ghosh, B Chatterjee, B Chakraborty, S Dalai, AK Pradhan