# Machine Learning in Healthcare

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/machine-learning-in-healthcare-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 339,485 |
| Description | This cluster of papers focuses on the application of deep learning techniques in healthcare, particularly in the analysis of electronic health records (EHR). The papers cover a wide range of topics including predictive modeling, patient similarity, disease risk prediction, medical concept embedding, and temporal data analysis. The goal is to leverage deep learning to improve healthcare decision-making and enable precision medicine. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | https://openalex.org/T13702 |
| Works | 45,314 |

## Topic researchers

Showing 12 of 20.

- [Douglas G. Altman](https://scholariq.org/researchers/douglas-g-altman/)
- [Christopher J L Murray](https://scholariq.org/researchers/christopher-j-l-murray/)
- [Geoffrey E. Hinton](https://scholariq.org/researchers/geoffrey-e-hinton/)
- [George Davey Smith](https://scholariq.org/researchers/george-davey-smith/)
- [Ronald C. Kessler](https://scholariq.org/researchers/ronald-c-kessler/)
- [Matthias Egger](https://scholariq.org/researchers/matthias-egger/)
- [John P. A. Ioannidis](https://scholariq.org/researchers/john-p-a-ioannidis/)
- [Karl Friston](https://scholariq.org/researchers/karl-friston/)
- [Chris Sander](https://scholariq.org/researchers/chris-sander/)
- [Lalit Dandona](https://scholariq.org/researchers/lalit-dandona/)
- [Valentı́n Fuster](https://scholariq.org/researchers/valent-n-fuster/)
- [Penny Whiting](https://scholariq.org/researchers/penny-whiting/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.