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CGSI 2024 Videos Now Available
The Department of Computational Medicine has sponsored the Computational Genomics Summer Institute (CGSI) with funding from the NIH since 2016. In July, more than 160 researchers and trainees from a number of disciplines (statistics, bioengineering, math, computer science, genetics, and others) came to UCLA to participate in CGSI 2024. Program director Dr.
New AI model efficiently reaches clinical-expert-level accuracy in complex medical scans
By Kevin McClanahan
Media Contact | David Sampson | DSampson@mednet.ucla.edu
UCLA researchers have developed a deep-learning framework that teaches itself quickly to automatically analyze and diagnose MRIs and other 3D medical images – with accuracy matching that of medical specialists in a fraction of the time. An article describing the work and the system’s capabilities is published in Nature Biomedical Engineering.
Congratulations to Rachel Mester and Apeksha Singh!
The Department of Computational Medicine and especially the Biomathematics Ph.D. program wants to congratulate Rachel Mester and Apeksha Singh for finishing their Ph.D. in Biomathematics.
Biomathematics PhD Students Mariana Harris Heredia and Xiangting Li Receive Dissertation Year Award
The Dissertation Year Award is intended to support doctoral students who are within one year of completing and filing their dissertation. This is the first time the Department of Computational Medicine has received two Dissertation Year Awards! The department is very proud of both Mariana and Xiangting and we look forward to the great work they will do during the upcoming academic year. Congratulations!
Biomath PhD program welcomes nine new students
This fall, the Department of Computational Medicine at UCLA welcomes nine new students to its Biomathematics Ph.D. program. The incoming students have a diverse backgrounds in mathematics and biology, and they aspire to integrate different disciplines in their research.
Vivek Agarwal
- Undergraduate Institution: University of Maryland
Bachelor of Science, Computer Science
Kai Akamatsu
Machine learning tool identifies rare, undiagnosed immune disorders through patients’ electronic health records
By Kevin McClanahan
Researchers say a machine learning tool can identify many patients with rare, undiagnosed diseases years earlier, potentially improving outcomes and reducing cost and morbidity. The findings, led by researchers at UCLA Health, are described in Science Translational Medicine.
Professor Ken Lange honored at annual symposium
UCLA Receives $4.6M Grant from The Warren Alpert Foundation to Launch Computational Biology/AI Training Program
UCLA has received a $4.6 million grant from The Warren Alpert Foundation to establish the Warren Alpert UCLA Computational Biology/AI Training and Retention Program.
UCLA SwabSeq Lab Completes 2 Million COVID-19 Diagnostic Tests
More than four years after the world first learned about COVID that led to an unprecedented global health crisis in modern history and upended life as we knew it, UCLA researchers behind the SwabSeq COVID-19 PCR test came together November 13 in honor of SwabSeq’s third anniversary and its milestone of reaching 2 million processed tests.
Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries
Biobanks that collect deep phenotypic and genomic data across many individuals have emerged as a key resource in human genetics. However, phenotypes in biobanks are often missing across many individuals, limiting their utility. We propose AutoComplete, a deep learning-based imputation method to impute or ‘fill-in’ missing phenotypes in population-scale biobank datasets. When applied to collections of phenotypes measured across ~300,000 individuals from the UK Biobank, AutoComplete substantially improved imputation accuracy over existing methods.