There’s also a separate folder for application assets (i.e., the images associated with some of the cards). All of the data seems to be stored in a SQLite database in ~Library/Application Support/Anki2/. Coding it upĪnki is a little bit weird regarding how it structures its data. While I couldn’t quite include my anatomy and histopathology cards (since those were just images), it seemed like there would be enough to actually make a graph out of the remaining cards I had left. Furthermore, individual cards were formatted in a “fill in the blank” format (aka “cloze deletion”) that can easily be parsed to get out unique keywords/phrases. For example, cards in the Anking deck are tagged by subject. More importantly, a lot of those cards had rich metadata associated with them. PlanĪfter some R&R during break, I noticed that I had reviewed over 8000 cards in Anki since starting school. In a phrase: boredom during winter break (and a need to do a fun CS project outside of research stuff and Advent of code…which became painful after day 19). That notion of connectedness led me to actually see how “connected” all the different concepts we were learning about actually were. In a paragraph: Medical school can really seem like you’re drinking from a firehose, and there were definitely times in my first semester when it felt like that However, after a couple of weeks, my friends and I noticed that the content would suddenly feel connected to other bits of content we learn, making it much easier to remember. Accordingly, I found myself using both resources. for microbiology, we split it up by system instead of tackling it as one big block of content like other schools/resources do). However, since UCLA is currently undergoing a curriculum change, it was difficult to find cards that 100% correlated to what we did in class (e.g. The predominant advice in the medical school anki community is to avoid making your own cards and rely on the Anking deck. This deck contains 40,000+ cards based on popular study aids such as Sketchy, Boards and Beyond, Pathoma, etc, that are pretty much engineered to help with Step 1 prep. In addition to the in-house (i.e., school-specific) cards that I make for studying, I also use a compilation of decks made based on 3rd party resources called the AnKing deck. To my surprise, the scheduling algorithm actually does work (though with some minor tweaks required for the massive amount of content associated with medical school), and I was able to do very well on my exams so far just by making sure I kept up with daily reviews (i.e., the cards that anki tells me I have to re-do) and doing practice questions provided by the school. Personally, I’ve found the Anki algorithm to be great for medical school so far ( and about 108k other people agree with me as of Jan 2022) since it has minimized the amount of time I need to do a dedicated review for exams. In practice, this means that any card you look at on anki will show up again at some period later based on a spaced-repetition learning algorithm. For those not familiar, Anki is basically a flashcard application with some neat scheduling features built in to ensure that you don’t forget cards over time. Classes actually started in September (after a month of covering basic sciences that were more or less done in undergrad), and I have been using Anki for my studying since then. Over the past few months, I’ve been working towards my MD at the David Geffen School of Medicine at UCLA.
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