Sparse Twin Support Vector Clustering Using Pinball Loss

Tanveer, M.; Gupta, Tarun; Shah, Miten; Richhariya, Bharat

doi:10.1109/jbhi.2021.3059910

Cited by 15 publications

(2 citation statements)

References 35 publications

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“…Sine previous AD diagnosis researches are developed in closed settings, the closed setting in Clinical AIBench is similar to the previous research (24,25,26,27,28,12,29,30,31). Only AD and CN subjects are included in the closed setting, and only the nuclear magnetic resonance instrument and historical medical records are available.…”

Section: Clinical Aibenchmentioning

confidence: 90%

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OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings

Huang

Wang

Tang

et al. 2021

Preprint

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This paper quantitatively reveals the state-of-the-art and state-of-the-practice AI systems only achieve acceptable performance on the stringent conditions that all categories of subjects are known, which we call closed clinical settings, but fail to work in real-world clinical settings. Compared to the diagnosis task in the closed setting, real-world clinical settings pose severe challenges, and we must treat them differently. We build a clinical AI benchmark named Clinical AIBench to set up real-world clinical settings to facilitate researches. We propose an open, dynamic machine learning framework and develop an AI system named OpenClinicalAI to diagnose diseases in real-world clinical settings. The first versions of Clinical AIBench and OpenClinicalAI target Alzheimer's disease. In the real-world clinical setting, OpenClinicalAI significantly outperforms the state-of-the-art AI system. In addition, OpenClinicalAI develops personalized diagnosis strategies to avoid unnecessary testing and seamlessly collaborates with clinicians. It is promising to be embedded in the current medical systems to improve medical services.

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Section: Clinical Aibenchmentioning

confidence: 90%

“…To the best of our knowledge, all state-of-the-art and state-of-the-practice Alzheimer's disease diagnosis AI researches are developed and evaluated in closed settings (27,28,12,29,30,31).…”

Section: The Performance Of Openclinicalai On Alzheimer's Disease Diagnosismentioning

confidence: 99%