Medical Technology

@theomitsa 11 months ago

https://arxiv.org/abs/2306.09968 ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data #MachineLearning, #DataScience, #ChatGPT @Khulood_Almani @enilev @EstelaMandela @KevinClarity @Shi4Tech @bimedotcom @RLDI_Lamy @Analytics_659 @JagersbergKnut

@freddytn 1 year ago

Shifting #MachineLearning for #healthcare from development to deployment & from models to data By A Zhang, L Xing, J Zou & J Wu Data-centric view of #innovation + challenges #health #medicine #datascience #artificialintelligence @natBME @NaturePortfolio https://www.nature.com/articles/s41551-022-00898-y

@odsc 2 years ago

Results published recently in Nature Medicine demonstrate that federated learning builds powerful AI models that generalize across healthcare institutions. #DataScience #FederatedLearning #Healthcare https://hubs.li/H0XF-170

@nelsonSpinto 2 years ago

My surprised face reading this article: Great work by @kdpsinghlab et al. Lesson learned: #DataScience models in medicine are going nowhere without thorough evaluation and post-implementation monitoring. https://twitter.com/jamainternalmed/status/1407005406514319361

@PinakiLaskar 3 years ago

Why are #machinelearning models trained to make medical decisions that perform at nearly the same level as human experts not in clinical use? https://www.linkedin.com/posts/pinakilaskar_machinelearning-algorithms-deeplearning-activity-6806429189512728576-8Dhl #BigData #Analytics #DataScience #Python #RStats #JavaScript #ReactJS #Serverless #Linux #Coding #100DaysofCode

@andrewdfeldman 3 years ago

Cerebras Systems today announced our collaboration with @AstraZeneca using Cerebras CS-1 to advance drug discovery – specifically training large-scale NLP models to enable rapid medical literature search on PubMed #AI #NLP #pharmatech #pharma #DL #datascience https://twitter.com/CerebrasSystems/status/1386710936891936772

@nasmoutiphd 4 years ago

Google developed Coral: a portable neural network accelerator. It will make it possible to use models locally without the need for cloud. Sending data to the cloud is a security risk for sensitive data (eg medical records). #MachineLearning #DataScience https://www.theverge.com/platform/amp/2020/1/14/21065141/google-coral-ai-edge-computing-products-applications-cloud?fbclid=IwAR1xGpoS5u-6qqSKDTBCztUlz5Os8KbFVg3aVTdHEXM1nQmEzvkvubv5BmU

@ewenharrison 4 years ago

Black box models are not acceptable for high stakes decisions in medicine. Models must be interpretable, not just explainable (explanations are wrong by definition). Here’s your great long-read for today by @CynthiaRudin https://arxiv.org/abs/1811.10154 #rstats #DataScience

@odsc 4 years ago

MIT develops a system that lets nonspecialists use machine learning models to make predictions for medical research, sales, and more. #DataScience #MachineLearning @MIT https://hubs.ly/H0jJypg0

@odsc 4 years ago

MIT develops a system that lets nonspecialists use machine learning models to make predictions for medical research, sales, and more. #DataScience #MachineLearning @MIT https://hubs.ly/H0jJxzD0

@infocents 7 years ago

2019 alternative payment models #Medicare unveils far-reaching overhaul. #p4q #p4p #DataScience https://goo.gl/NIn4Hb