Placental Clock DREAM Challenge

Develop a new clock to achieve greater accuracy in predicting gestational age!

Digitally-Derived Endpoints for Freezing-of-Gait Detection (DEFoGD) Challenge

Digitally-Derived Endpoints for Freezing-of-Gait Detection in Parkinson''s (PD)

MapMySpikes: Data Challenge

How do firing properties of a cell relate to its molecular cell type?

Medical Image De-Identification Benchmark (MIDI-B) Challenge

Assessment rule-based DICOM image de-identification (deID) algorithms

BraTS 2024

Adult brain gliomas. characterization

Automated Identification of Mod-Sev TBI Lesions

Traumatic Brain Injury characterization

Multi-Class Segmentation of Aortic Branches and Zones in CTA

Aorta medical imaging

Pelvic Bone Fragments with Injuries Segmentation Challenge

Pelvic fractures characterization

ToothFairy2: Multi-Structure Segmentation in CBCT Volumes

Multi-Structure Segmentation in CBCT Volumes

Ischemic Stroke Lesion Segmentation Challenge 2024

ischemic stroke prediction

AI4Life Microscopy Denoising Challenge

Unsupervised denoising of microscopy images

AutoPET III

Refine the automated segmentation of tumor lesions in PET/CT scans

The LEOPARD Challenge

Uncover finer morphological features' prognostic value

Abdominal Circumference Operator-agnostic UltraSound measurement

Fetal growth restriction prediction

Head and Neck Tumor Segmentation for MR-Guided Applications

Head and Neck Tumor Segmentation

🕹️ 🍄 MARIO : Monitoring AMD progression in OCT

Improve the planning of anti-VEGF treatments

Federated Tumor Segmentation (FeTS) 2024 Challenge

Benchmarking weight aggregation methods for federated training

DREAM olfactory mixtures prediction

Predicting smell from molecule features

precisionFDA Automated Machine Learning (AutoML) App-a-thon

Unlock new insights into its potential applications in healthcare and medicine

ISBI BodyMaps24: 3D Atlas of Human Body

Variations in organ sizes and shapes can indicate a range of medical conditions, from benign anomalies to life-threatening diseases. Precise organ volume measurement is fundamental for effective patient care, but manual organ contouring is extremely time-consuming and exhibits considerable variability among expert radiologists. Artificial Intelligence (AI) holds the promise of improving volume measurement accuracy and reducing manual contouring efforts. We formulate our challenge as a semantic segmentation task, which automatically identifies and delineates the boundary of various anatomical structures essential for numerous downstream applications such as disease diagnosis and treatment planning. Our primary goal is to promote the development of advanced AI algorithms and to benchmark the state of the art in this field. The BodyMaps challenge particularly focuses on assessing and improving the generalizability and efficiency of AI algorithms in medical segmentation across divers...

Cell Tracking Challenge 2024

Develop novel, robust cell segmentation and tracking algorithms

BraTS-ISBI 2024 - Generalizability Across Tumors Challenge

BraTS-GoAT Challenge: Generalizability Across Brain Tumor Segmentation Tasks

Diminished Reality for Emerging Applications in Medicine

Dataset of Synthetic Surgery Scenes: Photorealistic Operating Room Simulations

Harvard Rare Disease Hackathon 2024

Are you a student interested in using AI/ML to tackle rare diseases? Join us!