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@FanZhang_Jessie 2 years ago
Excitedto share that we are selected to receive a Translational Medicine Research Grant from @PhRMAfoundation @PhRMA! We will develop #Singlecell #MachineLearning methods to decipher myeloid phenotypes on the lung-synovium axis in RA #rheumatology Thank all my collaborators!!
@IoannaBouri 2 years ago
Hi! #minätutkin #machinelearning approaches that can help medical professionals analyze the cancer risks associated with different exposures and detect possible interactions. @helsinkiuni [so cool to read about everyone’s research] #research #phdresearch #phdchat
@HEARTinMagnet 2 years ago
We are shortly going to recruit a post-doc clinical scientist/research associate with previous experience in #CMR 🫀🧲, #coding, #medicalimaging, #Dicom, #DataAnalytics & #MachineLearning! This will be a unique opportunity for an enthusiastic person to join us! @uniofeastanglia
@maiamajumder 2 years ago
Fellow researchers in #AI, #machinelearning, & #datascience (among others): if you’re trying to do #COVID19 research & don’t have a single public or medical health practitioner on your team, please pause & reconsider. Interdisciplinary research demands interdisciplinary teams!
@ravi_b_parikh 3 years ago
Lastly, this was a huge lift that took operations, research, and clinician leadership by @lynn_schuchter Larry Shulman@mdraugelis Nina O'Connor & others. Fuller data to come in next few months. But I feel a LOT more hopeful abt #AI/#machinelearning in medicine after this effort
@IEEEXplore 4 years ago
In this @IEEEAccess article, learn about the success of #machinelearning algorithms at image recognition tasks in recent years. This article includes key research areas & applications of medical image classification, localization, detection, segmentation, & registration.
@atulbutte 4 years ago
Peter Chang: Let's get medical students to gain research skills in #AI and #machinelearning, to learn the specifics of applying these tools properly to medical data #UCaiBio
@raamana_ 5 years ago
Random tip: if a PI publishes over 25 papers/year (more than 2 papers/month), in a heavily data- and optimization-driven research e.g. #MachineLearning in medicine, without releasing their codebase or using public libraries, be HIGHLY skeptical about their results. #phdchat