Conclusion
In conclusion , the application of AI in healthcare has the potential to revolutionise the way we understand , diagnose , and treat diseases . AI algorithms are being used in various domains , such as drug discovery , clinical trials , and clinical research , to improve the efficiency , accuracy , and cost-effectiveness of healthcare . However , the use of AI healthcare also raises important ethical and technical challenges , such as data privacy , bias , interpretability , and security . Addressing these challenges is crucial to ensure that AI algorithms are fair , equitable , and secure in their application to biomedical data . Further research is needed to develop AI algorithms that are interpretable , transparent , and secure , and to address the ethical and legal questions surrounding the use of AI in healthcare .
REFERENCE
Liu , T ., Siegel , E . and Shen , D ., 2022 . Deep learning and medical image analysis for COVID-19 diagnosis and prediction . Annual Review of Biomedical Engineering , 24 , pp . 179-201 .
Voon , W ., Hum , Y . C ., Tee , Y . K ., Yap , W . S ., Salim , M . I . M ., Tan , T . S ., Mokayed , H . and Lai , K . W ., 2022 . Performance analysis of seven Convolutional Neural Networks ( CNNs ) with transfer learning for Invasive Ductal Carcinoma ( IDC ) grading in breast histopathological images . Scientific reports , 12 ( 1 ), p . 19200 . https :// doi . org / 10.1038 / s41598-022- 21848-3
Lee , G ., Nho , K ., Kang , B ., Sohn , K . A . and Kim , D ., 2019 . Predicting Alzheimer ’ s disease progression using multi-modal deep learning approach . Scientific reports , 9 ( 1 ), p . 1952 . https :// doi . org / 10.1038 / s41598-018-37769-z
Goh , C . H ., Wong , K . K ., Tan , M . P ., Ng , S . C ., Chuah , Y . D . and Kwan , B . H ., 2022 . Development of an effective clustering algorithm for older fallers . PLoS ONE , 17 ( 11 ), p . e0277966 . https :// doi . org / 10.1371 / journal . pone . 0277966
Murdoch , B ., 2021 . Privacy and artificial intelligence : challenges for protecting health information in a new era . BMC Medical Ethics , 22 ( 1 ), pp . 1-5 . https :// doi . org / 10.1186 / s12910-021-00687-3
Gundersen , T . and Bærøe , K ., 2022 . The future ethics of artificial intelligence in medicine : Making sense of collaborative models . Science and Engineering Ethics , 28 ( 2 ), p . 17 . https :// doi . org / 10.1007 / s11948-022-00369-2
Harrer , S ., Shah , P ., Antony , B . and Hu , J ., 2019 . Artificial intelligence for clinical trial design . Trends in Pharmacological Sciences , 40 ( 8 ), pp . 577-591 . https :// doi . org / 10.1016 / j . tips . 2019.05.005
Lee , J . -H ., P . -S . Chee , E . -H . Lim and C . -H . Tan , 2021 . “ Artificial Intelligence-Assisted Throat Sensor Using Ionic Polymer – Metal Composite ( IPMC ) Material .” Polymers 13 ( 18 ): 3041 . doi : 10.3390 / polym13183041 .
Lee , K . T ., P . S . Chee , E . H . Lim and C . C . Lim , 2022 . “ Artificial intelligence ( AI ) -driven smart glove for object recognition application .” Materials Today : Proceedings 64 : 1563-1568 . https :// doi . org / 10.1016 / j . matpr . 2021.12.473
O ’ Neil , C . ( 2016 ). “ Weapons of Math Destruction : How Big Data Increases Inequality and Threatens Democracy .” Crown , New York .
Pesapane , F ., Codari , M . and Sardanelli , F ., 2018 . Artificial intelligence in medical imaging : threat or opportunity ? Radiologists again at the forefront of innovation in medicine . European Radiology Experimental , 2 , pp . 1-10 .
ABI Research . New Report Identifies Leading AI Applications for Healthcare . 2018 . Available online : https :// www . abiresearch . com / press / aisave-healthcare-sector-us52-billion-2021 /
Lee , D ., 2019 . Effects of key value co-creation elements in the healthcare system : focusing on technology applications . Service Business , 13 ( 2 ), pp . 389-417 .
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