NEW #opensaccess paper "Evidence of unreliable data and poor data provenance in clinical prediction model research and clinical practice"
link.springer.com/article/10.1...
#researchintegrity #dataprovenance #predictionmodels #predictiveAI
link.springer.com/article/10.1...
#researchintegrity #dataprovenance #predictionmodels #predictiveAI
July 17, 2026 at 5:54 PM
NEW #opensaccess paper "Evidence of unreliable data and poor data provenance in clinical prediction model research and clinical practice"
link.springer.com/article/10.1...
#researchintegrity #dataprovenance #predictionmodels #predictiveAI
link.springer.com/article/10.1...
#researchintegrity #dataprovenance #predictionmodels #predictiveAI
New data looking at prediction models for #T1D #RiskScreening #PredictionModels #DiabetesResearch #Endocrinology #MedSky
Addressing type 1 diabetes prediction challenges: study compares trade-offs between cost, performance models and participant time and provides insights for tailored risk screening. #T1D #DiabetesResearch #RiskScreening link.springer.com/article/10.1... 🔓
Type 1 diabetes prediction in autoantibody-positive individuals: performance, time and money matter - Diabetologia
Aims/hypothesis Efficient prediction of clinical type 1 diabetes is important for risk stratification and monitoring of autoantibody-positive individuals. In this study, we compared type 1 diabetes pr...
link.springer.com
May 27, 2025 at 8:38 AM
New data looking at prediction models for #T1D #RiskScreening #PredictionModels #DiabetesResearch #Endocrinology #MedSky
ICYMI: "Clinical prediction models using machine learning in oncology: challenges and recommendations"
--> bmjoncology.bmj.com/content/4/1/...
#machinelearning #digitalhealth #predictionmodels #methodsmatter
--> bmjoncology.bmj.com/content/4/1/...
#machinelearning #digitalhealth #predictionmodels #methodsmatter
Clinical prediction models using machine learning in oncology: challenges and recommendations
Clinical prediction models are widely developed in the field of oncology, providing individualised risk estimates to aid diagnosis and prognosis. Machine learning methods are increasingly being used t...
bmjoncology.bmj.com
December 19, 2025 at 10:16 AM
ICYMI: "Clinical prediction models using machine learning in oncology: challenges and recommendations"
--> bmjoncology.bmj.com/content/4/1/...
#machinelearning #digitalhealth #predictionmodels #methodsmatter
--> bmjoncology.bmj.com/content/4/1/...
#machinelearning #digitalhealth #predictionmodels #methodsmatter
April 22, 2025 at 7:40 AM
Join us for a pre-conference course on 29th April: An Intro to Clinical Prediction Models & Sample Size Calculations! Learn from experts like Dr Joie Ensor & Prof Richard Riley. Only £50. More info: https://buff.ly/40hOPZ2. #PredictionModels #MEMTAB2025
Pre-conference Courses - MEMTAB 2025
buff.ly
January 2, 2025 at 3:12 PM
Join us for a pre-conference course on 29th April: An Intro to Clinical Prediction Models & Sample Size Calculations! Learn from experts like Dr Joie Ensor & Prof Richard Riley. Only £50. More info: https://buff.ly/40hOPZ2. #PredictionModels #MEMTAB2025
Comparing Radiation Effects on the Bladder and Rectum in Prostate Cancer Patients: With and Without Adjusting for Pre-Treatment Side Effects #prostatecancer #radiotherapy #toxicities #biomarkers #predictionmodels #VBA #IBDM #OAR #bladder #rectum ssrn.com/abstract=502...
January 26, 2025 at 9:30 AM
Comparing Radiation Effects on the Bladder and Rectum in Prostate Cancer Patients: With and Without Adjusting for Pre-Treatment Side Effects #prostatecancer #radiotherapy #toxicities #biomarkers #predictionmodels #VBA #IBDM #OAR #bladder #rectum ssrn.com/abstract=502...
PROBAST+AI is a refined tool for assessing prediction models.
🔍Extends PROBAST-2019 with 34 questions for bias and applicability.
DOI link: https://tnyp.me/uunnVBxx/s #PredictionModels #AI #HealthcareResearch https://doi.org/10.1136/bmj-2024-082505
🔍Extends PROBAST-2019 with 34 questions for bias and applicability.
DOI link: https://tnyp.me/uunnVBxx/s #PredictionModels #AI #HealthcareResearch https://doi.org/10.1136/bmj-2024-082505
August 12, 2026 at 12:01 PM
PROBAST+AI is a refined tool for assessing prediction models.
🔍Extends PROBAST-2019 with 34 questions for bias and applicability.
DOI link: https://tnyp.me/uunnVBxx/s #PredictionModels #AI #HealthcareResearch https://doi.org/10.1136/bmj-2024-082505
🔍Extends PROBAST-2019 with 34 questions for bias and applicability.
DOI link: https://tnyp.me/uunnVBxx/s #PredictionModels #AI #HealthcareResearch https://doi.org/10.1136/bmj-2024-082505
PROBAST+AI updates bias assessment for prediction models.
📊 Addresses 16 development & 18 evaluation signaling questions
DOI: https://tnyp.me/uunnVBxx/s #PredictionModels #Healthcare #MachineLearning https://doi.org/10.1136/bmj-2024-082505
📊 Addresses 16 development & 18 evaluation signaling questions
DOI: https://tnyp.me/uunnVBxx/s #PredictionModels #Healthcare #MachineLearning https://doi.org/10.1136/bmj-2024-082505
July 30, 2026 at 8:40 AM
PROBAST+AI updates bias assessment for prediction models.
📊 Addresses 16 development & 18 evaluation signaling questions
DOI: https://tnyp.me/uunnVBxx/s #PredictionModels #Healthcare #MachineLearning https://doi.org/10.1136/bmj-2024-082505
📊 Addresses 16 development & 18 evaluation signaling questions
DOI: https://tnyp.me/uunnVBxx/s #PredictionModels #Healthcare #MachineLearning https://doi.org/10.1136/bmj-2024-082505
Summary: PROBAST+AI updates the PROBAST tool for bias and applicability in prediction models using regression or AI methods.
#AI #PredictionModels #Healthcare #RiskOfBias #PROBAST
https://tnyp.me/uunnVBxx/s https://doi.org/10.1136/bmj-2024-082505
#AI #PredictionModels #Healthcare #RiskOfBias #PROBAST
https://tnyp.me/uunnVBxx/s https://doi.org/10.1136/bmj-2024-082505
July 23, 2026 at 8:26 AM
Summary: PROBAST+AI updates the PROBAST tool for bias and applicability in prediction models using regression or AI methods.
#AI #PredictionModels #Healthcare #RiskOfBias #PROBAST
https://tnyp.me/uunnVBxx/s https://doi.org/10.1136/bmj-2024-082505
#AI #PredictionModels #Healthcare #RiskOfBias #PROBAST
https://tnyp.me/uunnVBxx/s https://doi.org/10.1136/bmj-2024-082505
psychology psychiatry predicting.disorder mental.illness schizophrenia prodromal error predictionmodels type.I.error
January 7, 2025 at 12:18 AM
psychology psychiatry predicting.disorder mental.illness schizophrenia prodromal error predictionmodels type.I.error
FREE WEBINAR: Early Warning Systems for Coral Reefs: Machine Learning for Conservation - 4th June 2025
mauinow.com/2025/05/22/f...
#coralreefs #hawaii #machinelearning #predictionmodels #climatechange #coralhealth #ai #technology #marinescience #coral #marinebiology
mauinow.com/2025/05/22/f...
#coralreefs #hawaii #machinelearning #predictionmodels #climatechange #coralhealth #ai #technology #marinescience #coral #marinebiology
Free Webinar “Early Warning Systems for Coral Reefs: Machine Learning for Conservation” on June 4, 2025 | Maui Now
The Maui Nui Marine Resource Council will host its first quarterly “Know Your Ocean Speaker Series” on Wednesday, June 4, 2025 featuring Dr. Lisa McManus of the Hawaiʻi Institute of Marine Biology at…
mauinow.com
May 28, 2025 at 2:21 PM
FREE WEBINAR: Early Warning Systems for Coral Reefs: Machine Learning for Conservation - 4th June 2025
mauinow.com/2025/05/22/f...
#coralreefs #hawaii #machinelearning #predictionmodels #climatechange #coralhealth #ai #technology #marinescience #coral #marinebiology
mauinow.com/2025/05/22/f...
#coralreefs #hawaii #machinelearning #predictionmodels #climatechange #coralhealth #ai #technology #marinescience #coral #marinebiology
arXiv:2504.13576v1 Announce Type: new
Abstract: Aiming at the problems of low accuracy and large error fluctuation of traditional traffic flow predictionmodels when dealing with multi-scale temporal features and dynamic change patterns. this [1/4 of https://arxiv.org/abs/2504.13576v1]
Abstract: Aiming at the problems of low accuracy and large error fluctuation of traditional traffic flow predictionmodels when dealing with multi-scale temporal features and dynamic change patterns. this [1/4 of https://arxiv.org/abs/2504.13576v1]
April 21, 2025 at 6:04 AM
arXiv:2504.13576v1 Announce Type: new
Abstract: Aiming at the problems of low accuracy and large error fluctuation of traditional traffic flow predictionmodels when dealing with multi-scale temporal features and dynamic change patterns. this [1/4 of https://arxiv.org/abs/2504.13576v1]
Abstract: Aiming at the problems of low accuracy and large error fluctuation of traditional traffic flow predictionmodels when dealing with multi-scale temporal features and dynamic change patterns. this [1/4 of https://arxiv.org/abs/2504.13576v1]