Medical Technology

@Radiology_AI 10 months ago

Differences in data distribution may affect federated #DeepLearning model performance in medical image segmentation https://doi.org/10.1148/ryai.220082 @ND_CSE @hku_science @ZJU_China #FederatedLearning #AI #MachineLearning #AIME23 #AIME2023 https://t.co/Sg0Y2jheGy

@Radiology_AI 11 months ago

#AI model for 3D segmentation of rotator cuff muscles and corresponding intramuscular fat https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #MSKRad #ML #MachineLearning https://t.co/dQAYmlJEVV

@Radiology_AI 1 year ago

#AI model for 3D segmentation of rotator cuff muscles and corresponding intramuscular fat https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #ML #MachineLearning https://t.co/oNMCGLErOr

@medical_xpress 1 year ago

Optimizing sepsis treatment timing with a #machinelearning model @OhioState @NatMachIntell https://medicalxpress.com/news/2023-04-optimizing-sepsis-treatment-machine.html

@Radiology_AI 1 year ago

#AI model for 3D segmentation of rotator cuff muscles and corresponding intramuscular fat https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #DeepLearning #RotatorCuff #MachineLearning https://t.co/zDjQ4xANb8

@Radiology_AI 1 year ago

#AI model for 3D segmentation of rotator cuff muscles and corresponding intramuscular fat https://doi.org/10.1148/ryai.220132 @BrookeArmyMed @MedicineUVA #RotatorCuff #ML #MachineLearning https://t.co/4151Kb3NCk

@murrayfold 1 year ago

Immensely proud of our latest paper. It's definitely not just your standard "scientist builds ML model and claims it's brilliant" paper. @EPSRC_CMAC @ArticularEpsrc #medicinesmanufacturing #MachineLearning #AI https://doi.org/10.1039/D2DD00024E

@Radiology_AI 1 year ago

The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #ML #MachineLearning https://t.co/y3sZ38NIZ7

@Radiology_AI 1 year ago

The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #DeepLearning #ML #MachineLearning https://t.co/zkCddWgOZR

@Radiology_AI 1 year ago

The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #AI #MachineLearning https://t.co/SlT3r4lHqe

@Radiology_AI 1 year ago

A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #DeepLearning #MachineLearning https://t.co/924nXgpWwb

@Radiology_AI 1 year ago

A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #Transformers #ML #MachineLearning https://t.co/Yjh54EzRFg

@Radiology_AI 1 year ago

A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #DeepLearning #ML #MachineLearning https://t.co/cfC4OrFxC0

@Radiology_AI 1 year ago

The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #AI #ML #MachineLearning https://t.co/ij1qLOqOrw

@Radiology_AI 1 year ago

The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #Transformers #AI #MachineLearning https://t.co/68vIIKCDag

@Radiology_AI 1 year ago

The challenges of training a very large medical imaging #transformer model https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #BERT #DeepLearning #MachineLearning #AMIA2022 https://t.co/LvndChK6Cw

@Radiology_AI 1 year ago

A large-scale 3D #transformer model could reduce the amount of data needed to train and fine-tune medical imaging #AI models https://doi.org/10.1148/ryai.210284 @StanfordRad @StanfordMed #DeepLearning #ML #MachineLearning https://t.co/t0Vza8lPaU

@woojinrad 1 year ago

AI for medical imaging must be monitored for bias. Monitoring for bias will become more and more essential, just as monitoring for drift and #MachineLearning model decay. https://buff.ly/3VcUMBE @AuntMinnie #ImagingAI #AI #AIbias #ImagingInformatics https://t.co/d9SMbVuTWq

@bigmlcom 1 year ago

Using #MachineLearning to identify undiagnosable #cancers -- a new model that maps developmental pathways to tumor cells may unlock the identity of cancers of unknown primary. #Heathcare #MedicalDiagnosis https://news.mit.edu/2022/using-machine-learning-identify-undiagnosable-cancers-0901 https://t.co/4ptktVOHTg

@medical_xpress 1 year ago

#Suicide vulnerability index, #machinelearning model help predict counties' risk @penn_state https://doi.org/gqd8f8 https://medicalxpress.com/news/2022-06-suicide-vulnerability-index-machine-counties.html

@NeuyAi 2 years ago

Today our newest #Medical #AI model is ready for testing. This one covers rosacea, eczema, and basal cell carinoma. This now brings our dermatology models to 4. #data #ArtificialIntelligence #MachineLearning #datasciencejobs #Cancer #skincare #NEUYAI #NEUYVision #CancerResearch https://t.co/WAxh9qjS30

@yuanhypnosluo 2 years ago

Congratulations to @Mochersonmao, a talented faculty from Luo Lab at @NUFeinbergMed, on the new article in @JBI_Journal! MedGCN extends the general #GCN model to heterogeneous graphs and missing feature values in medical settings. #DeepLearning #MachineLearning https://twitter.com/JBI_Journal/status/1489645363447439365

@globaliqx 2 years ago

New #MachineLearning model could speed up the process of developing new medicines https://buff.ly/3Hp2MIy #AI #eHealth #IoT #DigitalTransformation #DeepLearning @JoannMoretti @PawlowskiMario @CurieuxExplorer @MargaretSiegien https://t.co/RiRllSfmzB

@freddytn 2 years ago

#ArtificialIntelligence system rapidly predicts how 2 proteins attach #MachineLearning model could help scientists speed dev of new meds & directly predict complex that will form 80-500X faster #health #medicine #biotech @MIT @MIT_CSAIL @AIHealthMIT https://news.mit.edu/2022/ai-predicts-protein-docking-0201

@marcusborba 2 years ago

#ArtificialIntelligence system rapidly predicts how two proteins will attach The #machinelearning model could help scientists speed the development of new medicines https://news.mit.edu/2022/ai-predicts-protein-docking-0201 @MIT #AI #DataScience #BigData #Analytics #womenwhocode #DeepLearning #100DaysofCode

@JordanJasuta 2 years ago

Looking forward to sharing a hybrid medical #nlp model at the R|gov conference on #AI in #government Dec 9! Tickets available at https://rstats.ai/gov/ @rstatsai @rstatsdc #rstats #rstatsgov (my model actually uses #python - but it's still #MachineLearning !) https://twitter.com/rstatsai/status/1466136832727564295

@NeurasysR 2 years ago

Deep learning model that can determine the level of dementia of a patient with Alzheimer's disease based on their MRI image. Project: https://github.com/NeurasysResearch/Alzheimer-MRI-Model- #DataScience #data #MachineLearning #open #Science #Python #100DaysOfCode #radiology #MRI #Medical #AI #Alzheimer https://t.co/M6lmEyI68L

@AkinleyeJoshua9 2 years ago

Yes, Location of the brain Tumor can be detected in real-time in a functional Magnetic Resonance Imagery, though the model isn't deployed yet #100DaysOfCode #MachineLearning #Python #JavaScriptDeveloper #medicine @google #neuroscience @TFBestPractices #DataScience #Neurology https://t.co/QSxgUWzP9z

@Michael_D_Moor 2 years ago

Preprint alert! Interested in #MachineLearning in #medicine and #sepsis? We developed and validated a #DeepLearning model for predicting sepsis across 5 ICU databases from 3 countries featuring 156k ICU stays and 783 patient years worth of monitoring data. A 🧵. 1/n https://t.co/4RL3UaXYIY

@Gradio 2 years ago

Demo of the Day: Using a U-net for finding abnormalities in #MRI scans. Dataset: https://www.kaggle.com/mateuszbuda/lgg-mri-segmentation Colab: https://colab.research.google.com/drive/1rNW2YH7DsI9mnbKtIMeolT86A3_q-3ie?authuser=1#scrollTo=Lhh1U3XHvEiC A #MachineLearning in #Medicine model 🩺 https://t.co/BkfrAjKRJq

@maxkelsen 2 years ago

Our Research Lab has developed a #machinelearning model that can rapidly diagnose glaucoma based off medical images, with an error rate less than half that of human doctors. #AI #glaucoma #MedTech #DigitalHealth https://www.brisbanetimes.com.au/national/queensland/ai-trained-to-spot-disease-that-sends-people-blind-20210706-p587ca.html

@DiagnosingML 2 years ago

External validation of a widely implemented Sepsis Prediction Model shows significantly poorer performance than reported by developers. https://ja.ma/3wXhG3s via @JAMAInternalMed #machinelearning #ethics #ethicalAI #health #AI #medicine @stacymcarter

@ipfconline1 2 years ago

[#HealthTech] Cardiovascular diseases: New computer model improves therapy https://medicalxpress.com/news/2021-01-cardiovascular-diseases-therapy.html @tugraz via @medical_xpress #AI #MachineLearning Cc @MHiesboeck @bobehayes @andi_staub @DeepLearn007 @ahier @Fabriziobustama @SpirosMargaris @sallyeaves https://t.co/UItx8rGvEY

@_Sivasai 3 years ago

Development of #MachineLearning Model Using #EHR Data 2 Identify #Antibiotics Use Among #Hospitalized #patients @rebsmoe @GermsAndNumbers @Deverick_A #MedTwitterAI #ML #ArtificialIntelligence #DHPSP #MedTwitter #MedTwitterAI #data #scicomm #MedTech #Medical #MedEd #AI #bigdata https://twitter.com/alvie_barr/status/1376917871125757953

@ipfconline1 3 years ago

@yourICM 3 years ago

5 key principles that should be remembered for smart use of #ArtificialIntelligence as adoption of #MachineLearning systems becomes more widespread in medical imaging: ➡️knowledge base ➡️metrics ➡️bias ➡️model fragility ➡️error-prone behavior #DataScience https://rdcu.be/cdI0d https://t.co/OvNVtwfl94

@adaihueze 3 years ago

I built a heart disease binary classification model based on some common factors and causatives. The article can be found here => https://lnkd.in/d94wfrP #Health #medicine #MachineLearning #DataScience #WomenWhoCode #100DaysOfCode #CodeNewbies #womenintech #WomenInSTEM

@BigDataQueen_me 3 years ago

Nature article: #DeepLearning model to detect early stage of glaucoma, trained on OCT images #bigDataQueen #Python #MachineLearning #AI #100DaysOfCode #DEVCommunity #IoT #womenintech #womeininStem #RStats #Biomed #ML #DataScience #neuralnetwork #medical https://www.nature.com/articles/s41598-020-76154-7 https://t.co/WObUNhRPvH

@Ronald_vanLoon 3 years ago

#ArtificialIntelligence model detects asymptomatic COVID-19 infections through cellphone-recorded coughs by Jennifer Chu @medical_xpress Read more https://bit.ly/3mKai6g #AI #MachineLearning #MI #DL #HealthTech Cc: @ieeeorg @ogrisel @dalithsteiger https://t.co/2Ban95ZQsp

@Abhishek4273 3 years ago

Tried training an image segmentation model on PanNuke dataset, an Open Pan-Cancer Histology Dataset - https://github.com/Tessellate-Imaging/Monk_Object_Detection/tree/master/application_model_zoo (Ex 51) Data - https://jgamper.github.io/PanNukeDataset/ #100DaysOfCode #100DaysOfMLCode #301DaysOfCode #MachineLearning #Python #git #medical #Cancer #opensource #AI https://t.co/rFQ5JcvZjt

@PGCgenetics 3 years ago

Predicting the likelihood of future #psychiatricdisorders based on training a #MachineLearning #ML #AI model using a handful of genetic variants is unsound science, and likely to lead to medical discrimination. Thread 1/9. Preprint: https://bit.ly/2GSjiq6

@DrLukeOR 3 years ago

"The medical #AI floodgates open, at a cost of $1000 per patient." My new blog post on the unexpected, important, and controversial decision for Medicare in the US to pay up to $1000 per case for a #machinelearning model to detect stroke on CT scans. https://lukeoakdenrayner.wordpress.com/2020/09/06/the-medical-ai-floodgates-open-at-a-cost-of-1000-per-patient/ https://t.co/byxRVZzXLD

@KirkDBorne 3 years ago

.@DeptVetAffairs tests #AI ‘to-go’ delivery model to assist its medical centers during #pandemic — using embeddable AI modules that efficiently integrate across different systems: https://dy.si/5oTQh —— #HealthTech #BigData #DataScience #MachineLearning #DigitalTransformation https://t.co/shzIeiS0ep

@YaleRadiology 4 years ago

Another honor for our Interventional Oncology Lab: #medstudent Nathan Chai has received the #RSNA Research Medical Student Grant! Nathan will develop a #MachineLearning model to predict HCC recurrence. Congrats Nathan & team! #futuredoctor @YaleMed @RSNA @dcmadoff @JuliusChapiro https://t.co/UyqV1qryjW