Excellent concept, but onboarding gap undermines learning
I like the core idea of this app—case-based diagnostic reasoning is exactly what trainees need. However, there is a critical issue with how scoring is presented versus how users are instructed.
There is no upfront explanation of how answers are graded. As a result, I initially approached cases by building a broad differential (which is a valid clinical strategy), assuming that having the correct diagnosis included would be sufficient.
Instead, the app grades heavily based on ranking and early prioritization, not just inclusion. In my case, I correctly identified the diagnosis, but because it was lower in my differential list, I received a score of 0/30.
This creates two problems:
1. Mismatch between user expectations and scoring system
2. False negative feedback, where correct reasoning is effectively scored as failure
This is not a knowledge issue—it’s a communication issue.
A brief onboarding or tutorial explaining:
- That differentials must be ranked by likelihood
- That earlier identification improves scoring
- How hints affect grading
would immediately resolve this.
As it stands, the app risks losing users early—especially trainees—because it feels like being graded incorrectly rather than being taught. Receiving a near-zero score despite identifying the correct diagnosis is discouraging and undermines trust in the feedback.
The tool has strong potential, but the lack of clear instructions actively detracts from the learning experience.
If clear guidance is added upfront, I would strongly consider revising this to a 5/5, because the underlying product is genuinely valuable.
There is no upfront explanation of how answers are graded. As a result, I initially approached cases by building a broad differential (which is a valid clinical strategy), assuming that having the correct diagnosis included would be sufficient.
Instead, the app grades heavily based on ranking and early prioritization, not just inclusion. In my case, I correctly identified the diagnosis, but because it was lower in my differential list, I received a score of 0/30.
This creates two problems:
1. Mismatch between user expectations and scoring system
2. False negative feedback, where correct reasoning is effectively scored as failure
This is not a knowledge issue—it’s a communication issue.
A brief onboarding or tutorial explaining:
- That differentials must be ranked by likelihood
- That earlier identification improves scoring
- How hints affect grading
would immediately resolve this.
As it stands, the app risks losing users early—especially trainees—because it feels like being graded incorrectly rather than being taught. Receiving a near-zero score despite identifying the correct diagnosis is discouraging and undermines trust in the feedback.
The tool has strong potential, but the lack of clear instructions actively detracts from the learning experience.
If clear guidance is added upfront, I would strongly consider revising this to a 5/5, because the underlying product is genuinely valuable.
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Love this app
Love the cases. Both interesting and relevant
MS2
Great exposure
Great application
I find this application awesome. It features great cases. There is a learning component to it and the ability to collaborate with others. The teaching points make it an academic exercise and allow one to build on their foundation of knowledge. I think it would be a great resource in the educational, post graduate, and professional settings. There are also points someone can accumulate which makes it fun like a game, too
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This is how medicine should be
I really like it. One learn while also providing help. Very nice.
