LoopdMed turns missed questions into high-yield rules and resurfaces them through active recall instead of letting them become forgotten notes.
Convert missed-question takeaways into review prompts.
Let review timing adapt as your recall history grows.
Keep spaced repetition tied to real practice misses.
Four seamless steps designed to sit right beside your daily practice blocks.
Snap or paste the question you missed from UWorld, AAMC, Amboss, or class exams. Drop it straight in.
Categorize why you missed it (Misread Stem, Logic Flaw, or Content Gap) and tag the topic or organ system.
Distill the explanation into a single, high-yield takeaway rule that solves future question variations.
FSRS-powered scheduling brings the rule back through active recall, adapting future timing as your review history grows.
Screenshots preserve the question, but they do not force retrieval. LoopdMed extracts a concise rule and turns it into something you can actively test.
The platform is designed around the moment after a missed question. Capture, classify, extract, then review before memory decay makes the lesson expensive to relearn.
FSRS models memory using variables such as item difficulty, memory stability, and current retrievability. Review outcomes provide new information, allowing later intervals to change rather than forcing every item onto the same calendar.
LoopdMed uses those checkpoints in its simplified product walkthrough because they make the review loop easy to understand. They are not a promise that every prompt will always follow three fixed intervals.
A broad flashcard deck can contain thousands of facts. LoopdMed narrows spaced review to the rules created by your own missed and uncertain questions, helping the daily queue reflect demonstrated weak points.
Scheduling begins only after the original explanation has been converted into something worth retrieving. A concise, transferable prompt gives the scheduler a cleaner learning target.
Compress the miss into one principle or decision rule that can be understood without reopening the full question explanation.
Ask for the rule, relationship, or reasoning check directly. Avoid prompts that can be answered only by recognizing the original wording.
Record whether you actually recalled the answer. Hesitation, a partial answer, and complete forgetting give different evidence about the memory.
The review history informs when the prompt should return, keeping weak rules closer while allowing stable rules to move farther apart.
This simplified example illustrates the behavior of adaptive scheduling. Exact intervals depend on the scheduler configuration and the learner’s review history.
The purpose of FSRS is not to create a prettier fixed calendar. It is to use review history to make future timing responsive to the learner and the item.
FSRS stands for Free Spaced Repetition Scheduler. It is a modern scheduling approach that estimates memory states and uses review history to choose future intervals.
No. Those dates are useful for illustrating an early review sequence, but genuine FSRS scheduling is adaptive. Exact due dates can change with item difficulty, recall outcomes, desired retention, and prior history.
Both can use modern spaced scheduling. LoopdMed begins with a missed QBank question and keeps the error tag, extracted rule, and recall prompt connected. Anki is a broader, highly configurable flashcard platform.
Complete the review when you return and grade the recall honestly. The useful signal is what you remembered at that moment; pretending a forgotten item was remembered can produce intervals that do not match your memory.
No. Spaced repetition helps retain lessons extracted from practice. New QBank questions are still necessary for applying knowledge, handling unfamiliar passages, and testing reasoning under exam conditions.
