Literature DB >> 33620208

Artificial Intelligence in Medical Sensors for Clinical Decisions.

Hossam Haick1, Ning Tang1.   

Abstract

Due to the limited ability of conventional methods and the limited perspective of human diagnostics, patients are often diagnosed incorrectly or at a late stage as their disease condition progresses. They may then undergo unnecessary treatments due to inaccurate diagnoses. In this Perspective, we offer a brief overview on the integration of nanotechnology-based medical sensors and artificial intelligence (AI) for advanced clinical decision support systems to help decision-makers and healthcare systems improve how they approach information, insights, and the surrounding contexts, as well as to promote the uptake of personalized medicine on an individualized basis. Relying on these milestones, wearable sensing devices could enable interactive and evolving clinical decisions that could be used for evidence-based analysis and recommendations as well as for personalized monitoring of disease progress and treatment. We present and discuss the ongoing challenges and future opportunities associated with AI-enabled medical sensors in clinical decisions.

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Year:  2021        PMID: 33620208     DOI: 10.1021/acsnano.1c00085

Source DB:  PubMed          Journal:  ACS Nano        ISSN: 1936-0851            Impact factor:   15.881


  4 in total

1.  A Convolutional Neural Network-Based Intelligent Medical System with Sensors for Assistive Diagnosis and Decision-Making in Non-Small Cell Lung Cancer.

Authors:  Xiangbing Zhan; Huiyun Long; Fangfang Gou; Xun Duan; Guangqian Kong; Jia Wu
Journal:  Sensors (Basel)       Date:  2021-11-30       Impact factor: 3.576

Review 2.  Diagnostic Approaches For COVID-19: Lessons Learned and the Path Forward.

Authors:  Maha Alafeef; Dipanjan Pan
Journal:  ACS Nano       Date:  2022-08-03       Impact factor: 18.027

Review 3.  End-to-end design of wearable sensors.

Authors:  H Ceren Ates; Peter Q Nguyen; Laura Gonzalez-Macia; Eden Morales-Narváez; Firat Güder; James J Collins; Can Dincer
Journal:  Nat Rev Mater       Date:  2022-07-22       Impact factor: 76.679

4.  Profiles of Volatile Biomarkers Detect Tuberculosis from Skin.

Authors:  Rotem Vishinkin; Rami Busool; Elias Mansour; Falk Fish; Ali Esmail; Parveen Kumar; Alaa Gharaa; John C Cancilla; Jose S Torrecilla; Girts Skenders; Marcis Leja; Keertan Dheda; Sarman Singh; Hossam Haick
Journal:  Adv Sci (Weinh)       Date:  2021-06-02       Impact factor: 16.806

  4 in total

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