What happens when you combine a medical student who has spent hours doing chart review with a data scientist? A Natural Language Processing (#NLP) solution to automate the chart review process! #AI #DataScience #MachineLearning #HealthTech https://www.linkedin.com/pulse/v-labs-learnings-intersection-healthcare-data-science-kumaresan
Did you see this? A review of public comments on a proposed FDA regulatory framework for modifications to #AI and #machinelearning based software as a medical device has found that 63% came from parties with financial ties to industry. http://ow.ly/hAWE50C5cIu https://t.co/aFTQHYcLAh
"In the future, our review process of #BigData research will include reviewers with such specific expertise." #duh Covid-19 studies based on flawed Surgisphere data force medical journals to review processes https://www.theguardian.com/world/2020/jun/12/covid-19-studies-based-on-flawed-surgisphere-data-force-medical-journals-to-review-processes?CMP=Share_AndroidApp_Tweet
✍️Automatic annotation of medical images is the holy grail of #AI in #Radiology. This paper describes #MachineLearning models to generate annotations for review & appeared to expedite annotation with high sensitivity at the expense of specificity. https://link.springer.com/article/10.1007/s10278-019-00299-9?wt_mc=alerts.TOCjournals&utm_source=toc&utm_medium=email&utm_campaign=toc_10278_33_2
A new @CellCellPress Special Review issue on #Therapeutics: #Cancer, #autoimmune #disease, #vaccines, #RareDisease #MachineLearning and #medicine, #CRISPR #AAV, #pharma #neurodegeneration - its all @ http://bit.ly/2V9mLV1 https://t.co/TXz3prO4yu
Reporting quality of studies using #MachineLearning models for medical diagnosis by @epi_afro "All studies in this review failed to use reporting guidelines, and a large proportion of them lacked adequate detail..." https://tinyurl.com/s37a59w
.@harvard_data Science Review has returned with its 1st issue of 2020! Check out this fresh batch of articles on the latest topics in #datascience: differential privacy in the 2020 census, trusting #algorithms, precision medicine, and more. #ReadUPScience http://mitsha.re/kK9g50yfhEN
tips to review #MachineLearning papers, esp. in #medicine & #neuroscience: -ask for a flowchart from raw data to final metrics! -don't assume CV (like repeated holdout) and advanced metrics (AUC) are implemented correctly. If you don't follow it drunk, they're likely wrong!
Read the review article, "Machine Learning in Medicine," and watch the full video describing the core structural changes and paradigm shifts in the #healthcare system that are necessary to enable the full promise of #machinelearning in medicine. https://nej.md/2K8xwEL https://t.co/9Rt6lUIPHF
Medical error is 3rd most common cause of death. #AI and #MachineLearning can warn doctors about things they need to review. #EmTechDigital https://t.co/hsMapfWYfO
Challenges and Opportunities of #BigData in #HealthCare: A Systematic Review http://medinform.jmir.org/2016/4/e38 #Analytics… https://twitter.com/i/web/status/800734335716442112
