X-Ray Differential Diagnosis

Developer: Mohammed Musa

Category: Medical

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100 installs

2.00 ratings

8.00 monthly active users

Revenue not available

X-Ray Differential Diagnosis Summary

X-Ray Differential Diagnosis is a mobile iOS app in Medical by Mohammed Musa. Released in Aug 2018 (7 years ago). It has 2.00 ratings with a 5.00★ (excellent) average. Based on AppGoblin estimates, it reaches roughly 8.00 monthly active users . Store metadata: updated Sep 4, 2018.

Store info: Last updated on App Store on Sep 4, 2018 .

SDKs, Trackers & Permissions

App not yet scanned for SDKs.

App Details

Store ID: 1431803518

First Released: 2018-08-22

Store Last Updated: 2018-09-04

In-App Purchases: No

Ads: No

Website: liixuos.com

App Store

Crawl Status: Success

AppGoblin First Crawled: 2022-12-07

AppGoblin Last Crawled: 2026-03-01

Ads & App-Ads.txt

Ads.txt Last Crawled: 2025-10-12

Ads.txt Crawl Status: Success

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The download and scan process is automated but can require manual troubleshooting. Feel free to reach out if your request does not complete in 24hrs or if you have any questions.

5★

Ratings: 2.00

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Screenshots

App Description

X-Ray Differential Diagnosis is intended for medical students, young doctors and other healthcare professionals. It provides a list of possible causes for each finding encountered in everyday medical practice and an account of their differential diagnosis. It contains information about almost 140 radiological findings. To take advantage of this app you must be able to read medical x-ray films by your own self.

The app is free, working offline and includes:
1.Chest imaging
2.Cardiac imaging
3.Gastrointestinal imaging
4.Urinary imaging
5.Musculoskeletal imaging

Our application has endeavored to ensure the accuracy of the data, but still no guarantee can be given that the content is 100% error free.

Note that the use of this app is limited to educational purposes only and it should not be used as a source on which medical decisions are based.

Suggestions and comments regarding errors or for further improvement would be appreciated.