Potential risk quantification from multiple biological factors via the inverse problem algorithm as an artificial intelligence tool in clinical diagnosis.
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| Title: | Potential risk quantification from multiple biological factors via the inverse problem algorithm as an artificial intelligence tool in clinical diagnosis. |
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| Authors: | Huang SH; Department of Medical Imaging and Radiological Sciences, Central Taiwan University of Science and Technology, Taichung, Taiwan.; Department of Nursing, Taichung Armed Forces General Hospital, Taichung, Taiwan., Peng BR; Department of Medical Imaging and Radiological Sciences, Central Taiwan University of Science and Technology, Taichung, Taiwan., Lin CS; Department of Radiology, BenQ Medical Center, The Affiliated BenQ Hospital of the Nanjing Medical University, Nanjing, Jiangsu, China., Tsai HC; Department of Nursing, Chung Shan Medical University, Taichung, Taiwan.; Department of Nursing, Taichung Armed Forces General Hospital, Taichung, Taiwan., Pan LF; Department of Medical Imaging and Radiological Sciences, Central Taiwan University of Science and Technology, Taichung, Taiwan.; Department of Cardiology, Taichung Armed Forces General Hospital, Taichung, Taiwan., Pan LK; Department of Medical Imaging and Radiological Sciences, Central Taiwan University of Science and Technology, Taichung, Taiwan. |
| Source: | Technology and health care : official journal of the European Society for Engineering and Medicine [Technol Health Care] 2023; Vol. 31 (S1), pp. 69-79. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: SAGE Publications Country of Publication: United States NLM ID: 9314590 Publication Model: Print Cited Medium: Internet ISSN: 1878-7401 (Electronic) Linking ISSN: 09287329 NLM ISO Abbreviation: Technol Health Care Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1878-7401 |
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| DOI: | 10.3233/THC-236008 |
