nghiaump

nghiaump's Stars

• rasbt/LLMs-from-scratch

  Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

  Language:Jupyter Notebook72k10.4k

• rsummers11/CADLab

  Imaging Biomarkers and Computer-Aided Diagnosis Laboratory

  Language:C++453184

• obendidi/X-ray-classification

  X-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2

  Language:Python11146

• SeHwanJoo/mmdetection_vinbig

  kaggle competition vinbigdata top 2% solution

  Language:Python4

• Scu-sen/VinBigData-Chest-X-ray-Abnormalities-Detection

  Language:Python291

• caiyu6666/DDAD

  [MICCAI 2022] Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays

  Language:Python543

• funnyzhou/REFERS

  Language:Jupyter Notebook11911

• oyxhust/HAM

  Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis

  Language:Python294

• shankara-93/VinBigData-Chest-X-ray-Abnormalities-Detection

  In this competition, you’ll automatically localize and classify 14 types of thoracic abnormalities from chest radiographs. You'll work with a dataset consisting of 18,000 scans that have been annotated by experienced radiologists. You can train your model with 15,000 independently-labeled images and will be evaluated on a test set of 3,000 images. These annotations were collected via VinBigData's web-based platform, VinLab. Details on building the dataset can be found in our recent paper “VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations”. If successful, you'll help build what could be a valuable second opinion for radiologists. An automated system that could accurately identify and localize findings on chest radiographs would relieve the stress of busy doctors while also providing patients with a more accurate diagnosis.

  Language:Jupyter Notebook1

• pierre-lavieille/abnormality-detection-x-ray

  Chest X-ray Abnormalities Detection: Automatically localize and classify thoracic abnormalities from chest radiographs - Research Application - End-to-end prediction and inference pipeline - Dash app to visualize result

  Language:Python4

• vbookshelf/COVID-19-CXR-Analyzer

  This flask web app uses a fine tuned Yolov5 model to detect and localize COVID-19 on chest x-rays.

  Language:Jupyter Notebook3

• eveningdong/cardiothoracic_ratio_estimation_dataset

  Wingspan Chest Organ Segmentation and Cardiothoracic Ratio (CTR) Estimation Dataset

  Language:Python3

• vantienpham/CXRAbnormalityLocalization

  🫁 Chest X-ray abnormalities localization via ensemble of deep convolutional neural networks

  Language:Python203

• ngdhuy/fit-cntn-ptudw-2122

  FIT@HCMUS - Web development - 2022

  Language:JavaScript6