Deep Learning Applications in Medicine: Enhancing Diagnosis and Patient Outcomes
DOI:
https://doi.org/10.70445/gjus.2.2.2025.31-52Keywords:
Deep learning, Medicine, Medical diagnosis, personalized medicine, Patient outcomes, Medical imaging, Predictive analyticsAbstract
Deep learning has transformed the modern medicine to accurately diagnose, treat patients with uniqueness, and provide better patient outcomes. With the use of big data in medicine, imaging, electronic health record and genomic data, deep learning models identify subtle features, disease progression, and aids in clinical decision-making. The uses can include medical imaging and pathology as well as predictive analytics, remote monitoring, and AI-assisted drug discovery. Although issues like data privacy, model interpretability, and algorithmic biasness persist, such new approaches as explainable AI, federated learning, and IoT integration have greater opportunities to be safe and effective to adopt. Deep learning is building a future in the field of accuracy, effectiveness, and patient-centric care.
References
[1]. Thakur GK, Thakur A, Kulkarni S, Khan N, Khan S. Deep learning approaches for medical image analysis and diagnosis. Cureus. 2024 May 2;16(5).
[2]. Usmani UA, Happonen A, Watada J. Enhancing medical diagnosis through deep learning and machine learning approaches in image analysis. InIntelligent systems conference 2023 Sep 7 (pp. 449-468). Cham: Springer Nature Switzerland.
[3]. Addimulam S, Mohammed MA, Karanam RK, Ying D, Pydipalli R, Patel B, Shajahan MA, Dhameliya N, Natakam VM. Deep learning-enhanced image segmentation for medical diagnostics. Malaysian Journal of Medical and Biological Research. 2020 Nov 25;7(2):145-52.
[4]. Asif S, Wenhui Y, ur-Rehman S, ul-ain Q, Amjad K, Yueyang Y, Jinhai S, Awais M. Advancements and prospects of machine learning in medical diagnostics: unveiling the future of diagnostic precision. Archives of Computational Methods in Engineering. 2025 Mar;32(2):853-83.
[5]. Raparthi M. Deep learning for personalized medicine-enhancing precision health with AI. Journal of Science & Technology. 2020 Dec 26;1(1):82-90.
[6]. Nazir A, Hussain A, Singh M, Assad A. Deep learning in medicine: advancing healthcare with intelligent solutions and the future of holography imaging in early diagnosis. Multimedia Tools and Applications. 2025 May;84(17):17677-740.
[7]. Singh AP, Nigam A, Kumar V. An analysis of deep learning algorithms for detection of pulmonary illness. In2025 2nd International Conference on Computational Intelligence, Communication Technology and Networking (CICTN) 2025 Feb 6 (pp. 349-354). IEEE.
[8]. Shobayo O, Saatchi R. Developments in deep learning artificial neural network techniques for medical image analysis and interpretation. Diagnostics. 2025 Apr 23;15(9):1072.
[9]. Kabir R, Syed HZ, Vinnakota D, Sivasubramanian M, Hitch G, Okello SA, Pulikkottil AT, Mahmud I, Dehghani L, Parsa AD. Deep learning for clinical decision-making and improved healthcare outcome. InDeep Learning in Personalized Healthcare and Decision Support 2023 Jan 1 (pp. 187-201). Academic Press.
[10]. Hussain I, Nazir MB. Mind matters: Exploring AI, machine learning, and deep learning in neurological health. International Journal of Advanced Engineering Technologies and Innovations. 2024;4(1):209-30.
[11]. Rajdeo P, Aronow B, Prasath VS. Deep learning-based multimodal spatial transcriptomics analysis for cancer. Advances in cancer research. 2024 Jan 1;163:1-38.
[12]. Horasan A, Güneş A. Advancing prostate cancer diagnosis: A deep learning approach for enhanced detection in MRI images. Diagnostics. 2024 Aug 27;14(17):1871.
[13]. Maki S, Furuya T, Inoue M, Shiga Y, Inage K, Eguchi Y, Orita S, Ohtori S. Machine learning and deep learning in spinal injury: a narrative review of algorithms in diagnosis and prognosis. Journal of clinical medicine. 2024 Jan 25;13(3):705.
[14]. Gasmi K, Ben Aoun N, Alsalem K, Ltaifa IB, Alrashdi I, Ammar LB, Mrabet M, Shehab A. Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique. Frontiers in neuroinformatics. 2024 Nov 26;18:1444650.
[15]. Du J, Cang Y, Zhou T, Hu J, He W. Deep learning with HM-VGG: AI strategies for multi-modal image analysis. In2024 3rd International Symposium on Sensor Technology and Control (ISSTC) 2024 Oct 25 (pp. 290-294). IEEE.
[16]. Kumar RR, Shankar SV, Jaiswal R, Ray M, Budhlakoti N, Singh KN. Advances in deep learning for medical image analysis: a comprehensive investigation. Journal of Statistical Theory and Practice. 2025 Mar;19(1):9.
[17]. Abualigah L, Alomari SA, Almomani MH, Zitar RA, Saleem K, Migdady H, Snasel V, Smerat A, Ezugwu AE. Artificial intelligence-driven translational medicine: a machine learning framework for predicting disease outcomes and optimizing patient-centric care. Journal of translational medicine. 2025 Mar 10;23(1):302.
[18]. Huang SC, Pareek A, Seyyedi S, Banerjee I, Lungren MP. Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines. NPJ digital medicine. 2020 Oct 16;3(1):136.
[19]. Hosseinzadeh M, Khoshvaght P, Sadeghi S, Asghari P, Varzeghani AN, Mohammadi M, Mohammadi H, Lansky J, Lee SW. A model for epileptic seizure diagnosis using the combination of ensemble learning and deep learning. IEEE Access. 2024 Sep 10;12:137132-43.
[20]. Mulani AO, Deshmukh M, Jadhav V, Chaudhari K, Mathew AA, Salunkhe S. Transforming Drug Therapy with Deep Learning: The Future of Personalized Medicine. Drug Research. 2025 Oct;75(08):326-33.
[21]. Alwiyah A, Setyowati W. A comprehensive survey of machine learning applications in medical image analysis for artificial vision. International Transactions on Artificial Intelligence. 2023 Nov 25;2(1):90-8.
[22]. Javed H, El-Sappagh S, Abuhmed T. Robustness in deep learning models for medical diagnostics: security and adversarial challenges towards robust AI applications. Artificial Intelligence Review. 2024 Nov 8;58(1):12.
[23]. Whig P, Kasula BY, Yathiraju N, Jain A, Sharma S. Revolutionizing gender-specific healthcare: harnessing deep learning for transformative solutions. InTransforming gender-based healthcare with AI and machine learning 2024 Dec 24 (pp. 14-26). CRC Press.
[24]. Baji A. Enhancing healthcare predictions with deep learning models. InProceedings of the AAAI Conference on Artificial Intelligence 2024 Mar 24 (Vol. 38, No. 21, pp. 23729-23730).
[25]. Reis TC. Deep learning in oncology: Transforming cancer diagnosis, prognosis, and treatment. Emerging Trends in Drugs, Addictions, and Health. 2025 Dec 1;5:100171.
[26]. Saeed A, Husnain A, Rasool S, Gill AY. Healthcare Revolution: How AI and Machine Learning Are Changing Medicine. Journal Research of Social Science, Economics & Management. 2023 Oct 1;3(3).
[27]. Gracious LA, Jasmine RM, Pooja E, Anish TP, Johncy G, Subramanian RS. Machine learning and deep learning transforming healthcare: An extensive exploration of applications, algorithms, and prospects. In2023 4th IEEE Global Conference for Advancement in Technology (GCAT) 2023 Oct 6 (pp. 1-6). IEEE.
[28]. Rane N, Choudhary SP, Rane J. Ensemble deep learning and machine learning: applications, opportunities, challenges, and future directions. Studies in Medical and Health Sciences. 2024 Jul 4;1(2):18-41.
[29]. Fatima S. Improving healthcare outcomes through machine learning: Applications and challenges in big data analytics. International Journal of Advanced Research in Engineering Technology & Science. 2024;11.
[30]. Kothinti RR. The role of deep learning in radiology and medical imaging: improving diagnostic accuracy. International Journal of Academic Research and Development. 2024;9:128-43.
[31]. Chianumba EC, Ikhalea N, Mustapha AY, Forkuo AY, Osamika D. Exploring the role of AI and machine learning in improving healthcare diagnostics and personalized medicine. Journal of Frontiers in Multidisciplinary Research. 2023 Jan;4(1):177-82.
[32]. Sadr H, Nazari M, Khodaverdian Z, Farzan R, Yousefzadeh-Chabok S, Ashoobi MT, Hemmati H, Hendi A, Ashraf A, Pedram MM, Hasannejad-Bibalan M. Unveiling the potential of artificial intelligence in revolutionizing disease diagnosis and prediction: a comprehensive review of machine learning and deep learning approaches. European journal of medical research. 2025 May 26;30(1):418.
[33]. Patra RC, Saritha G, Raghuwanshi GA, Parthiban P, Ashok V. Recent advances, challenges, and applications of deep learning in healthcare systems for medical diagnosis and treatment. In2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS) 2023 Nov 1 (pp. 716-724). IEEE.
[34]. Bhavsar KA, Abugabah A, Singla J, AlZubi AA, Bashir AK. A comprehensive review on medical diagnosis using machine learning. Computers, Materials and Continua. 2021 Feb 5;67(2):1997-2014.
[35]. Swanson K, Wu E, Zhang A, Alizadeh AA, Zou J. From patterns to patients: advances in clinical machine learning for cancer diagnosis, prognosis, and treatment. Cell. 2023 Apr 13;186(8):1772-91.
[36]. Alharbe N, Almalki M. IoT-enabled healthcare transformation leveraging deep learning for advanced patient monitoring and diagnosis. Multimedia Tools and Applications. 2025 Jun;84(19):21331-44.
[37]. Krčadinac O, Stojaković N. The application of deep learning in medicine: Benefits, challenges, and future prospects. Journal of UUNT: Informatics and Computer Sciences. 2024 Dec 29;1(1):19-25.
[38]. Lau, Billy Pik Lik, et al. “A Survey of Data Fusion in Smart City Applications.” Information Fusion, vol. 52, Dec. 2019, pp. 357–374, https://doi.org/10.1016/j.infus.2019.05.004.
[39]. Irshad RR, Hussain S, Sohail SS, Zamani AS, Madsen DØ, Alattab AA, Ahmed AAA, Norain KAA, Alsaiari OAS (2023) A Novel IoT-Enabled Healthcare Monitoring Framework and Improved Grey Wolf Optimization Algorithm-Based Deep Convolution Neural Network Model for Early Diagnosis of Lung Cancer. Sensors 23:2932. https://doi.org/10.3390/s23062932
[40]. Chaitanya B, Devi PN, Lakhanpal S, Mohammad Q, Geetha BT. Multi-modal medical image fusion for enhanced diagnosis using deep learning in the cloud. In2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI) 2023 Dec 29 (Vol. 1, pp. 1-7). IEEE.
[41]. Vedula J, Kakani TA, Gupta R, Mohammed M, Hudani K, Logeshwaran J. Optimizing Disease Diagnosis and Treatment Through AI and Deep Learning Algorithms. In2025 6th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV) 2025 Jun 17 (pp. 98-102). IEEE.
[42]. Gayap HT, Akhloufi MA. Deep machine learning for medical diagnosis, application to lung cancer detection: a review. BioMedInformatics. 2024 Jan 18;4(1):236-84.
[43]. Kolluri VE. The impact of machine learning on patient diagnosis accuracy: Investigating. International Journal of Emerging Technologies and Innovative Research, ISSN. 2024:2349-5162.
[44]. Islam MR, Kabir MM, Mridha MF, Alfarhood S, Safran M, Che D (2023) Deep Learning-Based IoT System for Remote Monitoring and Early Detection of Health Issues in Real-Time. Sensors 23:5204. https://doi.org/10.3390/s23115204
[45]. Malik P, Dureja A, Dureja A, Rathore RS, Malhotra N. Enhancing intracranial hemorrhage diagnosis through deep learning models. Procedia Computer Science. 2024 Jan 1;235:1664-73.
[46]. Taghados Z, Azimifar Z, Monsefi M, Jahromi MA. CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification—leveraging deep learning models for enhanced diagnostic accuracy. BMC cancer. 2025 Apr 3;25(1):607.
[47]. Padhi A, Agarwal A, Saxena SK, Katoch CD. Transforming clinical virology with AI, machine learning and deep learning: a comprehensive review and outlook. VirusDisease. 2023 Sep;34(3):345-55.
[48]. R. Singh, P. A. Mishra, A. Prakash, K. Tongkachok, M. Upadhyaya and M. Kalyan Chakravarthi, "Smart Device for Efective Communication in the Healthcare System," 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), Chennai, India, 2022, pp. 1–6, https://doi.org/10.1109/ICSES55317.2022.9914093.
[49]. Yao IZ, Dong M, Hwang WY. Deep learning applications in clinical cancer detection: a review of implementation challenges and solutions. Mayo clinic proceedings: digital health. 2025 Jul 18:100253.
[50]. Pantha Y. Enhancing Diagnostic Accuracy in Medicine Using Artificial Intelligence: a Deep Learning Approach. J. Enhanc. Heat Transf., no. 2024 Nov.
[51]. Kourou K, Exarchos KP, Papaloukas C, Sakaloglou P, Exarchos T, Fotiadis DI. Applied machine learning in cancer research: A systematic review for patient diagnosis, classification and prognosis. Computational and structural biotechnology journal. 2021 Jan 1;19:5546-55.
[52]. Adam MA, Mukhtar A. Heartfelt insights: AI and machine learning applications for cardiac wellness. International Journal of Advanced Engineering Technologies and Innovations. 2024;4(1):231-47.
[53]. Kannan KD, Jagatheesaperumal SK, Kandala RN, Lotfaliany M, Alizadehsanid R, Mohebbi M. Advancements in machine learning and deep learning for early detection and management of mental health disorder. arXiv preprint arXiv:2412.06147. 2024 Dec 9.
[54]. Surendran A, Daigavane P, Shrivastav S, Kamble R, Sanchla AD, Bharti L, Shinde M, Shrivastav Sr S. The future of orthodontics: deep learning technologies. Cureus. 2024 Jun 10;16(6).
[55]. Alsayat A, Mahmoud AA, Alanazi S, Mostafa AM, Alshammari N, Alrowaily MA, Shabana H, Ezz M. Enhancing cardiac diagnostics: A deep learning ensemble approach for precise ECG image classification. Journal of Big Data. 2025 Jan 19;12(1):7.
[56]. Shokoohi H, LeSaux MA, Roohani YH, Liteplo A, Huang C, Blaivas M. Enhanced point‐of‐care ultrasound applications by integrating automated feature‐learning systems using deep learning. Journal of ultrasound in medicine. 2019 Jul;38(7):1887-97.
[57]. Cakmak Y, Pacal I. Enhancing breast cancer diagnosis: A comparative evaluation of machine learning algorithms using the Wisconsin dataset. Journal of Operations Intelligence. 2025 May 6;3(1):180-201.
[58]. Fernandes JN, Cardoso VE, Comesana-Campos A, Pinheira A. Comprehensive review: machine and deep learning in brain stroke diagnosis. Sensors. 2024 Jul 4;24(13):4355.
[59]. Ramkumar G, Sujatha V, Raja B, TamilSelvi M, Balaji A, Kumar AK. An Experiment to Develop an Enhanced Medical Image Security by using Deep Learning Assisted Crypto Policy. In2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE) 2023 Nov 1 (pp. 1-8). IEEE.
