Applications of Artificial Intelligence in Health Sciences
References
Tarcan, G. Y., Balçık, P. Y., & Sebik, N. B. (2024). Türkiye ve Dünyada Sağlık Hizmetlerinde Yapay Zekâ. Mersin Üniversitesi Tıp Fakültesi Lokman Hekim Tıp Tarihi ve Folklorik Tıp Dergisi, 14(1), 50-60.
Liu, P. R., Lu, L., Zhang, J. Y., Huo, T. T., Liu, S. X., & Ye, Z. W. (2021). Application of artificial intelligence in medicine: an overview. Current Medical Science, 41(6), 1105-1115.
Freeman, K., Geppert, J., Stinton, C., Todkill, D., Johnson, S., Clarke, A., & Taylor-Phillips, S. (2021). Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy. bmj, 374.
Ali, I., Muzammil, M., Haq, I. U., Amir, M., & Abdullah, S. (2021). Deep feature selection and decision level fusion for lungs nodule classification. IEEE Access, 9, 18962-18973.
Ting, D. S., Peng, L., Varadarajan, A. V., Keane, P. A., Burlina, P. M., Chiang, M. F., ... & Wong, T. Y. (2019). Deep learning in ophthalmology: the technical and clinical considerations. Progress in retinal and eye research, 72, 100759.
Mishra, N. K., Singh, P., & Joshi, S. D. (2021). Automated detection of COVID-19 from CT scan using convolutional neural network. Biocybernetics and biomedical engineering, 41(2), 572-588.
Bai, L., Zhang, Y., Wang, P., Zhu, X., Xiong, J. W., & Cui, L. (2022). Improved diagnosis of rheumatoid arthritis using an artificial neural network. Scientific Reports, 12(1), 9810.
Nguyen, D. T., Kang, J. K., Pham, T. D., Batchuluun, G., & Park, K. R. (2020). Ultrasound image-based diagnosis of malignant thyroid nodule using artificial intelligence. Sensors, 20(7), 1822.
Trasolini, R., & Byrne, M. F. (2021). Artificial intelligence and deep learning for small bowel capsule endoscopy. Digestive Endoscopy, 33(2), 290-297.
Wells, A., Patel, S., Lee, J. B., & Motaparthi, K. (2021). Artificial intelligence in dermatopathology: Diagnosis, education, and research. Journal of cutaneous pathology, 48(8), 1061-1068.
Hu, W., Li, C., Li, X., Rahaman, M. M., Ma, J., Zhang, Y., ... & Grzegorzek, M. (2022). GasHisSDB: A new gastric histopathology image dataset for computer aided diagnosis of gastric cancer. Computers in biology and medicine, 142, 105207.
Maier-Hein, L., Eisenmann, M., Sarikaya, D., März, K., Collins, T., Malpani, A., ... & Speidel, S. (2022). Surgical data science–from concepts toward clinical translation. Medical image analysis, 76, 102306.
Ponsiglione, A. M., Zaffino, P., Ricciardi, C., Di Laura, D., Spadea, M. F., De Tommasi, G., ... & Amato, F. (2024). Combining simulation models and machine learning in healthcare management: strategies and applications. Progress in Biomedical Engineering, 6(2), 022001.
Lalmuanawma, S., Hussain, J., & Chhakchhuak, L. (2020). Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review. Chaos, Solitons & Fractals, 139, 110059.
Priya, S., Tripathi, G., Singh, D. B., Jain, P., & Kumar, A. (2022). Machine learning approaches and their applications in drug discovery and design. Chemical Biology & Drug Design, 100(1), 136-153.
Gurung, A. B., Ali, M. A., Lee, J., Farah, M. A., & Al-Anazi, K. M. (2021). An updated review of computer-aided drug design and its application to COVID-19. BioMed research international, 2021.
Ghaednia, H., Fourman, M. S., Lans, A., Detels, K., Dijkstra, H., Lloyd, S., ... & Schwab, J. H. (2021). Augmented and virtual reality in spine surgery, current applications and future potentials. The Spine Journal, 21(10), 1617-1625.
Deng Z, Xiang N, Pan J. State of the Art in Immersive Interactive Technologies for Surgery Simulation: A Review and Prospective. Bioengineering (Basel). 2023 Nov 23;10(12):1346. doi: 10.3390/bioengineering10121346. PMID: 38135937; PMCID: PMC10740891.
Briganti, G., & Le Moine, O. (2020). Artificial intelligence in medicine: today and tomorrow. Frontiers in medicine, 7, 509744.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology, 2(4).
Turing, A. M. (2009). Computing machinery and intelligence (pp. 23-65). Springer Netherlands.
Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. Metabolism, 69, S36-S40.
Noorbakhsh-Sabet, N., Zand, R., Zhang, Y., & Abedi, V. (2019). Artificial intelligence transforms the future of health care. The American journal of medicine, 132(7), 795-801.
Iqbal, J. D., & Vinay, R. (2022). Are we ready for Artificial Intelligence in Medicine?. Swiss medical weekly, 152(1920), w30179-w30179.
Nash, F. A. (1954). Differential diagnosis: an apparatus to assist the logical faculties. The Lancet, 263(6817), 874-875.
De Dombal, F. T., Leaper, D. J., Staniland, J. R., McCann, A. P., & Horrocks, J. C. (1972). Computer-aided diagnosis of acute abdominal pain. Br Med J, 2(5804), 9-13.
Garcia-Vidal, C., Sanjuan, G., Puerta-Alcalde, P., Moreno-García, E., & Soriano, A. (2019). Artificial intelligence to support clinical decision-making processes. EBioMedicine, 46, 27-29.
Dlamini, Z., Francies, F. Z., Hull, R., & Marima, R. (2020). Artificial intelligence (AI) and big data in cancer and precision oncology. Computational and structural biotechnology journal, 18, 2300-2311.
Tomita, K., Nagao, R., Touge, H., Ikeuchi, T., Sano, H., Yamasaki, A., & Tohda, Y. (2019). Deep learning facilitates the diagnosis of adult asthma. Allergology International, 68(4), 456-461.
Eckardt, J. N., Röllig, C., Metzeler, K., Kramer, M., Stasik, S., Georgi, J. A., ... & Middeke, J. M. (2023). Prediction of complete remission and survival in acute myeloid leukemia using supervised machine learning. Haematologica, 108(3), 690.
Freeman, K., Geppert, J., Stinton, C., Todkill, D., Johnson, S., Clarke, A., & Taylor-Phillips, S. (2021). Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy. bmj, 374.
Alhasan, M., & Hasaneen, M. (2021). Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic. Computerized Medical Imaging and Graphics, 91, 101933.
Stoel, B. (2020). Use of artificial intelligence in imaging in rheumatology–current status and future perspectives. RMD open, 6(1), e001063.
Abadir, A. P., Ali, M. F., Karnes, W., & Samarasena, J. B. (2020). Artificial intelligence in gastrointestinal endoscopy. Clinical endoscopy, 53(2), 132.
Mori, Y., Kudo, S. E., Mohmed, H. E., Misawa, M., Ogata, N., Itoh, H., ... & Mori, K. (2019). Artificial intelligence and upper gastrointestinal endoscopy: Current status and future perspective. Digestive endoscopy, 31(4), 378-388.
Cui, M., & Zhang, D. Y. (2021). Artificial intelligence and computational pathology. Laboratory Investigation, 101(4), 412-422.
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V., & Madabhushi, A. (2019). Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology. Nature reviews Clinical oncology, 16(11), 703-715.
Kuo, Y. H., Chan, N. B., Leung, J. M., Meng, H., So, A. M. C., Tsoi, K. K., & Graham, C. A. (2020). An integrated approach of machine learning and systems thinking for waiting time prediction in an emergency department. International journal of medical informatics, 139, 104143.
Hong, N., Liu, C., Gao, J., Han, L., Chang, F., Gong, M., & Su, L. (2022). State of the art of machine learning–enabled clinical decision support in intensive care units: Literature review. JMIR Medical Informatics, 10(3), e28781.
Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC medical informatics and decision making, 21, 1-23.
Bajwa, J., Munir, U., Nori, A., & Williams, B. (2021). Artificial intelligence in healthcare: transforming the practice of medicine. Future healthcare journal, 8(2), e188.
Akalın, B., & Veranyurt, Ü. (2020). Sağlikta Dijitalleşme ve Yapay Zekâ. SDÜ Sağlık Yönetimi Dergisi, 2(2), 128-137.
Liu, P. R., Lu, L., Zhang, J. Y., Huo, T. T., Liu, S. X., & Ye, Z. W. (2021). Application of artificial intelligence in medicine: an overview. Current Medical Science, 41(6), 1105-1115.
Freeman, K., Geppert, J., Stinton, C., Todkill, D., Johnson, S., Clarke, A., & Taylor-Phillips, S. (2021). Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy. bmj, 374.
Ali, I., Muzammil, M., Haq, I. U., Amir, M., & Abdullah, S. (2021). Deep feature selection and decision level fusion for lungs nodule classification. IEEE Access, 9, 18962-18973.
Ting, D. S., Peng, L., Varadarajan, A. V., Keane, P. A., Burlina, P. M., Chiang, M. F., ... & Wong, T. Y. (2019). Deep learning in ophthalmology: the technical and clinical considerations. Progress in retinal and eye research, 72, 100759.
Mishra, N. K., Singh, P., & Joshi, S. D. (2021). Automated detection of COVID-19 from CT scan using convolutional neural network. Biocybernetics and biomedical engineering, 41(2), 572-588.
Bai, L., Zhang, Y., Wang, P., Zhu, X., Xiong, J. W., & Cui, L. (2022). Improved diagnosis of rheumatoid arthritis using an artificial neural network. Scientific Reports, 12(1), 9810.
Nguyen, D. T., Kang, J. K., Pham, T. D., Batchuluun, G., & Park, K. R. (2020). Ultrasound image-based diagnosis of malignant thyroid nodule using artificial intelligence. Sensors, 20(7), 1822.
Trasolini, R., & Byrne, M. F. (2021). Artificial intelligence and deep learning for small bowel capsule endoscopy. Digestive Endoscopy, 33(2), 290-297.
Wells, A., Patel, S., Lee, J. B., & Motaparthi, K. (2021). Artificial intelligence in dermatopathology: Diagnosis, education, and research. Journal of cutaneous pathology, 48(8), 1061-1068.
Hu, W., Li, C., Li, X., Rahaman, M. M., Ma, J., Zhang, Y., ... & Grzegorzek, M. (2022). GasHisSDB: A new gastric histopathology image dataset for computer aided diagnosis of gastric cancer. Computers in biology and medicine, 142, 105207.
Maier-Hein, L., Eisenmann, M., Sarikaya, D., März, K., Collins, T., Malpani, A., ... & Speidel, S. (2022). Surgical data science–from concepts toward clinical translation. Medical image analysis, 76, 102306.
Ponsiglione, A. M., Zaffino, P., Ricciardi, C., Di Laura, D., Spadea, M. F., De Tommasi, G., ... & Amato, F. (2024). Combining simulation models and machine learning in healthcare management: strategies and applications. Progress in Biomedical Engineering, 6(2), 022001.
Lalmuanawma, S., Hussain, J., & Chhakchhuak, L. (2020). Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review. Chaos, Solitons & Fractals, 139, 110059.
Priya, S., Tripathi, G., Singh, D. B., Jain, P., & Kumar, A. (2022). Machine learning approaches and their applications in drug discovery and design. Chemical Biology & Drug Design, 100(1), 136-153.
Gurung, A. B., Ali, M. A., Lee, J., Farah, M. A., & Al-Anazi, K. M. (2021). An updated review of computer-aided drug design and its application to COVID-19. BioMed research international, 2021.
Ghaednia, H., Fourman, M. S., Lans, A., Detels, K., Dijkstra, H., Lloyd, S., ... & Schwab, J. H. (2021). Augmented and virtual reality in spine surgery, current applications and future potentials. The Spine Journal, 21(10), 1617-1625.
Deng Z, Xiang N, Pan J. State of the Art in Immersive Interactive Technologies for Surgery Simulation: A Review and Prospective. Bioengineering (Basel). 2023 Nov 23;10(12):1346. doi: 10.3390/bioengineering10121346. PMID: 38135937; PMCID: PMC10740891.
Briganti, G., & Le Moine, O. (2020). Artificial intelligence in medicine: today and tomorrow. Frontiers in medicine, 7, 509744.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and vascular neurology, 2(4).
Turing, A. M. (2009). Computing machinery and intelligence (pp. 23-65). Springer Netherlands.
Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. Metabolism, 69, S36-S40.
Noorbakhsh-Sabet, N., Zand, R., Zhang, Y., & Abedi, V. (2019). Artificial intelligence transforms the future of health care. The American journal of medicine, 132(7), 795-801.
Iqbal, J. D., & Vinay, R. (2022). Are we ready for Artificial Intelligence in Medicine?. Swiss medical weekly, 152(1920), w30179-w30179.
Nash, F. A. (1954). Differential diagnosis: an apparatus to assist the logical faculties. The Lancet, 263(6817), 874-875.
De Dombal, F. T., Leaper, D. J., Staniland, J. R., McCann, A. P., & Horrocks, J. C. (1972). Computer-aided diagnosis of acute abdominal pain. Br Med J, 2(5804), 9-13.
Garcia-Vidal, C., Sanjuan, G., Puerta-Alcalde, P., Moreno-García, E., & Soriano, A. (2019). Artificial intelligence to support clinical decision-making processes. EBioMedicine, 46, 27-29.
Dlamini, Z., Francies, F. Z., Hull, R., & Marima, R. (2020). Artificial intelligence (AI) and big data in cancer and precision oncology. Computational and structural biotechnology journal, 18, 2300-2311.
Tomita, K., Nagao, R., Touge, H., Ikeuchi, T., Sano, H., Yamasaki, A., & Tohda, Y. (2019). Deep learning facilitates the diagnosis of adult asthma. Allergology International, 68(4), 456-461.
Eckardt, J. N., Röllig, C., Metzeler, K., Kramer, M., Stasik, S., Georgi, J. A., ... & Middeke, J. M. (2023). Prediction of complete remission and survival in acute myeloid leukemia using supervised machine learning. Haematologica, 108(3), 690.
Freeman, K., Geppert, J., Stinton, C., Todkill, D., Johnson, S., Clarke, A., & Taylor-Phillips, S. (2021). Use of artificial intelligence for image analysis in breast cancer screening programmes: systematic review of test accuracy. bmj, 374.
Alhasan, M., & Hasaneen, M. (2021). Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic. Computerized Medical Imaging and Graphics, 91, 101933.
Stoel, B. (2020). Use of artificial intelligence in imaging in rheumatology–current status and future perspectives. RMD open, 6(1), e001063.
Abadir, A. P., Ali, M. F., Karnes, W., & Samarasena, J. B. (2020). Artificial intelligence in gastrointestinal endoscopy. Clinical endoscopy, 53(2), 132.
Mori, Y., Kudo, S. E., Mohmed, H. E., Misawa, M., Ogata, N., Itoh, H., ... & Mori, K. (2019). Artificial intelligence and upper gastrointestinal endoscopy: Current status and future perspective. Digestive endoscopy, 31(4), 378-388.
Cui, M., & Zhang, D. Y. (2021). Artificial intelligence and computational pathology. Laboratory Investigation, 101(4), 412-422.
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V., & Madabhushi, A. (2019). Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology. Nature reviews Clinical oncology, 16(11), 703-715.
Kuo, Y. H., Chan, N. B., Leung, J. M., Meng, H., So, A. M. C., Tsoi, K. K., & Graham, C. A. (2020). An integrated approach of machine learning and systems thinking for waiting time prediction in an emergency department. International journal of medical informatics, 139, 104143.
Hong, N., Liu, C., Gao, J., Han, L., Chang, F., Gong, M., & Su, L. (2022). State of the art of machine learning–enabled clinical decision support in intensive care units: Literature review. JMIR Medical Informatics, 10(3), e28781.
Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC medical informatics and decision making, 21, 1-23.
Bajwa, J., Munir, U., Nori, A., & Williams, B. (2021). Artificial intelligence in healthcare: transforming the practice of medicine. Future healthcare journal, 8(2), e188.
Akalın, B., & Veranyurt, Ü. (2020). Sağlikta Dijitalleşme ve Yapay Zekâ. SDÜ Sağlık Yönetimi Dergisi, 2(2), 128-137.
Pages
113-122
Published
April 23, 2024
Copyright (c) 2024 Academician Publishing Book Portal
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1.
Kadiroğlu Z. Applications of Artificial Intelligence in Health Sciences. In: Kadiroğlu AK, editor. General Internal Medicine VI (Spring) [Internet]. Türkiye: Academician Publishing Book DOI Portal; 2024 [cited 2026 Jul. 13]. pp. 113-22. Available from: https://omp35.books.akademisyen.net/index.php/akya/catalog/book/3053/chapter/13734
