Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment

被引:135
作者
Khanna, Narendra N. [1 ]
Maindarkar, Mahesh A. [2 ,3 ]
Viswanathan, Vijay [4 ]
Fernandes, Jose Fernandes E. [5 ]
Paul, Sudip [3 ]
Bhagawati, Mrinalini [3 ]
Ahluwalia, Puneet [6 ]
Ruzsa, Zoltan [7 ]
Sharma, Aditya [8 ]
Kolluri, Raghu [9 ]
Singh, Inder M. [2 ]
Laird, John R. [10 ]
Fatemi, Mostafa [11 ]
Alizad, Azra [12 ]
Saba, Luca [13 ]
Agarwal, Vikas [14 ]
Sharma, Aman [14 ]
Teji, Jagjit S. [15 ]
Al-Maini, Mustafa [16 ]
Rathore, Vijay [17 ]
Naidu, Subbaram [18 ]
Liblik, Kiera [19 ]
Johri, Amer M. [19 ]
Turk, Monika [20 ]
Mohanty, Lopamudra [21 ]
Sobel, David W. [22 ]
Miner, Martin [23 ]
Viskovic, Klaudija [24 ]
Tsoulfas, George [25 ]
Protogerou, Athanasios D. [26 ]
Kitas, George D. [27 ,28 ]
Fouda, Mostafa M. [29 ]
Chaturvedi, Seemant [30 ]
Kalra, Mannudeep K. [31 ]
Suri, Jasjit S. [2 ]
机构
[1] Indraprastha APOLLO Hosp, Dept Cardiol, New Delhi 110001, India
[2] Stroke Monitoring & Diagnost Div, AtheroPoint, Roseville, CA 95661 USA
[3] North Eastern Hill Univ, Dept Biomed Engn, Shillong 793022, India
[4] MV Diabet Ctr, Chennai 600013, India
[5] Univ Lisbon, Dept Vasc Surg, P-1649004 Lisbon, Portugal
[6] Max Super Specialty Hosp, Max Inst Canc Care, New Delhi 110017, India
[7] Univ Szeged, Fac Med, Invas Cardiol Div, H-6720 Szeged, Hungary
[8] Univ Virginia, Div Cardiovasc Med, Charlottesville, VA 22904 USA
[9] Ohio Hlth Heart & Vasc, Columbus, OH 43214 USA
[10] Heart & Vasc Inst, Adventist Hlth St Helena, St Helena, CA 94574 USA
[11] Mayo Clin Coll Med & Sci, Dept Physiol & Biomed Engn, Rochester, MN 55905 USA
[12] Mayo Clin, Coll Med & Sci, Dept Radiol, Rochester, MN 55905 USA
[13] Azienda Osped Univ, Dept Radiol, I-40138 Cagliari, Italy
[14] SGPGIMS, Dept Immunol, Lucknow 226014, India
[15] Ann & Robert H Lurie Childrens Hosp Chicago, Chicago, IL 60611 USA
[16] Allergy Clin Immunol & Rheumatol Inst, Toronto, ON L4Z 4C4, Canada
[17] AtheroPoint LLC, Roseville, CA 95661 USA
[18] Univ Minnesota, Elect Engn Dept, Duluth, MN 55812 USA
[19] Queens Univ, Dept Med, Div Cardiol, Kingston, ON K7L 3N6, Canada
[20] Hanse Wissenschaftskolleg Inst Adv Study, D-27753 Delmenhorst, Germany
[21] ABES Engn Coll, Dept Comp Sci, Ghaziabad 201009, India
[22] Natl Kapodistrian Univ Athens, Rheumatol Unit, Athens 15772, Greece
[23] Miriam Hosp Providence, Mens Hlth Ctr, Providence, RI 02906 USA
[24] Univ Hosp Infect Dis, Dept Radiol & Ultrasound, Zagreb 10000, Croatia
[25] Aristotele Univ Thessaloniki, Dept Surg, Thessaloniki 54124, Greece
[26] Natl & Kapodistrian Univ Athens, Dept Pathophysiol, Cardiovasc Prevent & Res Unit, Athens 15772, Greece
[27] Dudley Grp NHS Fdn Trust, Acad Affairs, Dudley DY1 2HQ, England
[28] Univ Manchester, Arthrit Res UK Epidemiol Unit, Manchester M13 9PL, England
[29] Idaho State Univ, Dept Elect & Comp Engn, Pocatello, ID 83209 USA
[30] Univ Maryland, Sch Med, Dept Neurol & Stroke Program, Baltimore, MD 21201 USA
[31] Harvard Med Sch, Dept Radiol, Boston, MA 02115 USA
关键词
artificial intelligence; deep learning; machine learning; diagnosis; treatment; cost-effectiveness; health economics; AI pruning; AI explainability; AI bias; recommendations; OVARIAN TUMOR CHARACTERIZATION; THYROID LESION CLASSIFICATION; MACHINE LEARNING FRAMEWORK; TISSUE CHARACTERIZATION; RISK STRATIFICATION; CAROTID ULTRASOUND; ATHEROSCLEROTIC PLAQUE; ERECTILE DYSFUNCTION; STROKE RISK; DISEASE;
D O I
10.3390/healthcare10122493
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Motivation: The price of medical treatment continues to rise due to (i) an increasing population; (ii) an aging human growth; (iii) disease prevalence; (iv) a rise in the frequency of patients that utilize health care services; and (v) increase in the price. Objective: Artificial Intelligence (AI) is already well-known for its superiority in various healthcare applications, including the segmentation of lesions in images, speech recognition, smartphone personal assistants, navigation, ride-sharing apps, and many more. Our study is based on two hypotheses: (i) AI offers more economic solutions compared to conventional methods; (ii) AI treatment offers stronger economics compared to AI diagnosis. This novel study aims to evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment, and then compare it to the traditional or non-AI-based approaches. Methodology: PRISMA was used to select the best 200 studies for AI in healthcare with a primary focus on cost reduction, especially towards diagnosis and treatment. We defined the diagnosis and treatment architectures, investigated their characteristics, and categorized the roles that AI plays in the diagnostic and therapeutic paradigms. We experimented with various combinations of different assumptions by integrating AI and then comparing it against conventional costs. Lastly, we dwell on three powerful future concepts of AI, namely, pruning, bias, explainability, and regulatory approvals of AI systems. Conclusions: The model shows tremendous cost savings using AI tools in diagnosis and treatment. The economics of AI can be improved by incorporating pruning, reduction in AI bias, explainability, and regulatory approvals.
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页数:38
相关论文
共 199 条
[1]   Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging [J].
Abdel Razek, Ahmed Abdel Khalek ;
Alksas, Ahmed ;
Shehata, Mohamed ;
AbdelKhalek, Amr ;
Abdel Baky, Khaled ;
El-Baz, Ayman ;
Helmy, Eman .
INSIGHTS INTO IMAGING, 2021, 12 (01)
[2]  
Acharya R, 2008, ARTECH HSE BIOINF BI, P1
[3]   Evolutionary Algorithm-Based Classifier Parameter Tuning for Automatic Ovarian Cancer Tissue Characterization and Classification [J].
Acharya, U. R. ;
Mookiah, M. R. K. ;
Sree, S. Vinitha ;
Yanti, R. ;
Martis, R. J. ;
Saba, L. ;
Molinari, F. ;
Guerriero, S. ;
Suri, J. S. .
ULTRASCHALL IN DER MEDIZIN, 2014, 35 (03) :237-245
[4]   Cost-Effective and Non-Invasive Automated Benign & Malignant Thyroid Lesion Classification in 3D Contrast-Enhanced Ultrasound Using Combination of Wavelets and Textures: A Class of ThyroScan™ Algorithms [J].
Acharya, U. R. ;
Faust, O. ;
Sree, S. V. ;
Molinari, F. ;
Garberoglio, R. ;
Suri, J. S. .
TECHNOLOGY IN CANCER RESEARCH & TREATMENT, 2011, 10 (04) :371-380
[5]   Computer-Aided Diagnostic System for Detection of Hashimoto Thyroiditis on Ultrasound Images From a Polish Population [J].
Acharya, U. Rajendra ;
Sree, S. Vinitha ;
Krishnan, M. Muthu Rama ;
Molinari, Filippo ;
Zieleznik, Witold ;
Bardales, Ricardo H. ;
Witkowska, Agnieszka ;
Suri, Jasjit S. .
JOURNAL OF ULTRASOUND IN MEDICINE, 2014, 33 (02) :245-253
[6]   Ovarian Tumor Characterization and Classification Using Ultrasound-A New Online Paradigm [J].
Acharya, U. Rajendra ;
Sree, S. Vinitha ;
Saba, Luca ;
Molinari, Filippo ;
Guerriero, Stefano ;
Suri, Jasjit S. .
JOURNAL OF DIGITAL IMAGING, 2013, 26 (03) :544-553
[7]   Atherosclerotic plaque tissue characterization in 2D ultrasound longitudinal carotid scans for automated classification: a paradigm for stroke risk assessment [J].
Acharya, U. Rajendra ;
Mookiah, Muthu Rama Krishnan ;
Sree, S. Vinitha ;
Afonso, David ;
Sanches, Joao ;
Shafique, Shoaib ;
Nicolaides, Andrew ;
Pedro, L. M. ;
Fernandes e Fernandes, J. ;
Suri, Jasjit S. .
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2013, 51 (05) :513-523
[8]   Understanding symptomatology of atherosclerotic plaque by image-based tissue characterization [J].
Acharya, U. Rajendra ;
Faust, Oliver ;
Sree, Vinitha S. ;
Alvin, A. P. C. ;
Krishnamurthi, Ganapathy ;
Seabra, Jose C. R. ;
Sanches, Joao ;
Suri, Jasjit S. .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2013, 110 (01) :66-75
[9]   Ovarian Tumor Characterization using 3D Ultrasound [J].
Acharya, U. Rajendra ;
Sree, S. Vinitha ;
Krishnan, M. Muthu Rama ;
Saba, Luca ;
Molinari, Filippo ;
Guerriero, Stefano ;
Sun, Jasjit S. .
TECHNOLOGY IN CANCER RESEARCH & TREATMENT, 2012, 11 (06) :543-552
[10]   An Accurate and Generalized Approach to Plaque Characterization in 346 Carotid Ultrasound Scans [J].
Acharya, U. Rajendra ;
Faust, Oliver ;
Sree, S. Vinitha ;
Molinari, Filippo ;
Saba, Luca ;
Nicolaides, Andrew ;
Suri, Jasjit S. .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2012, 61 (04) :1045-1053