tree-based algorithms, and pattern growth algorithms. The Apriori algorithm, the Eclat algorithm, and the FP-Growth algorithm are the most popular algorithms for the three categories, respectively.
Challenges and opportunities with using electronic medical records for large-scale psychiatry research Phenotyping in psychiatric research Future considerations for optimising the use of electronic medical records in psychiatry Conclusion References Acknowledgements Author information Ethics declarations Additional info...
To address these specific challenges effectively, we proposed a new patient data encoding method. This method is designed to fully accommodate the unique characteristics of patient data, enabling a more comprehensive understanding and interpretation of such information. Comparison with existing pre-trained...
To overcome these challenges, we propose to transform EHR data into embedding vectors17, thus uncoupling the data from the individual patient. The downstream machine learning tasks would use the embeddings vector as summary data rather than individual patient data. Our use of embedding in this study...
foraccuratediagnosisandtreatment[9,10].Despitethecrucialimportanceofthisdynamic,patient- centereddiagnosticprocess,thereisascarcityofresearchassessingtheabilityoflargelanguage models(LLMs)tosimulatethisinteraction. Toaddressabovechallenges,weintroduceAIHospital,aLLM-poweredmulti-agentframework thatsimulatesreal-worlddyna...
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The challenges of accurate gene prediction and enumeration are further aggravated in large genomes that contain highly repetitive transposable elements (TEs). Yet TEs play a substantial role in genome evolution and are themselves an important subject of study. Repeat annotation, based on counting occurr...
In particular, we expect that algorithms with the following properties may perform favorably in the benchmark challenges. Since most symptoms in the ICD-11 and DSM-V are shared between two or more disorders, the occurrence of multiple diagnoses is highly correlated. While it is possible to ...
To capture the distribution of disease prevalence across age and sex, we computed disease prevalence curves by dividing the total number of disease codes (ICD codes) within each age-sex stratum by the number of enrolled patients matching these demographics (see Methods part 1 for the precise defi...
make it computationally feasible to analyze large biobank cohorts. We have applied GATE to 871 TTE phenotypes in the UK Biobank data with White British ancestry, which were constructed based on PheCodes mapped to ICD codes and have at least 500 events. The genome-wide summary statistics are ...