Neural networks in healthcare

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Bolus Dose EP. 02

In this episodes we give an overview of neural networks and how they’re used in healthcare. This includes the following topics: 

• Definition of neural networks and a high level explanation of their structure 

• Overview of the development of neural networks and use in healthcare 

• How neural networks are implemented 

• Limitations and considerations for their use  

Some resources and papers we discuss: 

Some of the first applications of neural networks in medicine:

• Diagnosis of 14 conditions from chest X-ray: Rajpurkar, P. et al. Deep learning for chest radiograph diagnosis: a retrospective comparison of the chexnext algorithm to practicing radiologists. PLoS Med. 15, e1002686 (2018). 

• Diagnosis of diabetic retinopathy: Gulshan V, Peng L, Coram M, Stumpe MC, Wu D, Narayanaswamy A, Venugopalan S, Widner K, Madams T, Cuadros J, Kim R, Raman R, Nelson PC, Mega JL, Webster DR. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA. 2016 Dec 13;316(22):2402-2410. 

• Diagnosis of melanoma: Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017 Feb 2;542(7639):115-118. doi: 10.1038/nature21056. Epub 2017 Jan 25. Erratum in: Nature. 2017 Jun 28;546(7660):686. doi: 10.1038/nature22985. PMID: 28117445; PMCID: PMC8382232. 

Opinion regarding use of AI to detect unrecognised patterns from CXR: Topol EJ. AI-enabled opportunistic medical scan interpretation. Lancet. 2024 May 11;403(10439):1842. doi: 10.1016/S0140-6736(24)00924-3. PMID: 38735291.

Cases where CNNs have made inferences from unrelated / confounding aspects of images:

• Oakden-Rayner L, Dunnmon J, Carneiro G, Ré C. Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging. Proc ACM Conf Health Inference Learn (2020). 2020 Apr;2020:151-159. doi: 10.1145/3368555.3384468. PMID: 33196064; PMCID: PMC7665161.

• Winkler JK, Fink C, Toberer F, Enk A, Deinlein T, Hofmann-Wellenhof R, Thomas L, Lallas A, Blum A, Stolz W, Haenssle HA. Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition. JAMA Dermatol. 2019 Oct 1;155(10):1135-1141.

COMPOSER Sepsis Trial: Boussina, A., Shashikumar, S.P., Malhotra, A. et al. Impact of a deep learning sepsis prediction model on quality of care and survival. npj Digit. Med. 7, 14 (2024).

Articles outlining human-computer interaction with CNNs:

• Han SS, Park I, Eun Chang S, Lim W, Kim MS, Park GH, Chae JB, Huh CH, Na JI. Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders. J Invest Dermatol. 2020 Sep;140(9):1753-1761. doi: 10.1016/j.jid.2020.01.019. Epub 2020 Mar 31 

• Jabbour S, Fouhey D, Shepard S, et al. Measuring the Impact of AI in the Diagnosis of Hospitalized Patients: A Randomized Clinical Vignette Survey Study. JAMA. 2023;330(23):2275–2284.

• Yu, F., Moehring, A., Banerjee, O. et al. Heterogeneity and predictors of the effects of AI assistance on radiologists. Nat Med 30, 837–849 (2024).

Examples of bias in imaging:

• Seyyed-Kalantari L, Zhang H, McDermott MBA, Chen IY, Ghassemi M. Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations. Nat Med. 2021 Dec;27(12):2176-2182. doi: 10.1038/s41591-021-01595-0. Epub 2021 Dec 10. PMID: 34893776; PMCID: PMC8674135.

• Gichoya JW, Banerjee I, Bhimireddy AR, Burns JL, Celi LA, Chen LC, Correa R, Dullerud N, Ghassemi M, Huang SC, Kuo PC, Lungren MP, Palmer LJ, Price BJ, Purkayastha S, Pyrros AT, Oakden-Rayner L, Okechukwu C, Seyyed-Kalantari L, Trivedi H, Wang R, Zaiman Z, Zhang H. AI recognition of patient race in medical imaging: a modelling study. Lancet Digit Health. 2022 Jun;4(6):e406-e414. doi: 10.1016/S2589-7500(22)00063-2. Epub 2022 May 11. PMID: 35568690; PMCID: PMC9650160.