early-detection 开源项目推荐（52 个）

TSCenter /awesome-time-series-papers

来自顶级人工智能场所的最新时间序列论文和代码的精彩列表。

hw538 /cfDNAPro

cfDNAPro specializes in standardized and robust cfDNA fragmentomic analysis

COVID-19-AI-Research-Project /AI-Classification

Open source Artificial Intelligence for COVID-19 detection/early detection. Includes Convolutional Neural Networks (CNN) & Generative Adversarial Networks (GAN)

SentryPeer /SentryPeerHQ

Fraud Detection for VoIP. Use SentryPeer® HQ to help prevent VoIP cyberattacks and fraudulent VoIP phone calls (toll fraud) at https://sentrypeer.com

DebeshJha /Kvasir-SEG

Kvasir-SEG: A Segmented Polyp Dataset

aaronstone1699 /parkinson-s-diagnosis

proposed early detection method for parkinson's disease using deep learning on MRI dataset

DhilipSanjay /Human-Biomechanic-Analysis

Deep Learning Models for the Early Detection of Parkinson’s Disease using the motor-based symptoms.

AyushBinjola1 /Swar-Setu

SwarSetu is an AI-powered multilingual platform that helps in the early detection and support of learning disabilities like dyslexia, dysgraphia, and dyscalculia through interactive assessments, voice support, and role-based dashboards for parents and teachers.

aimaster-dev /Blood-Brain-Detect-System

This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.

AFLucas-UOM /AI-Early-Detection-System-for-Dyslexia-ADHD

Proof-of-concept behavioural analysis system for early detection of dyslexia and ADHD using spelling pattern evaluation, sentence rewriting similarity analysis, and keyboard/mouse interaction monitoring.

andrewli77 /DISC

This repository contains an implementation of DISC, an algorithm for learning DFAs for multiclass sequence classification.

Anil951 /Early-detection-of-mental-health

This project develops a predictive model to identify early signs of mental health issues in adolescents using social media activity, school performance, health records, and an AI chatbot. It analyzes emotional tone, academic changes, and health data, offering personalized recommendations and resources for mental wellness.

atharvaaalok /EWS-MultipleWindow-Method

Research on developing a new method for determining the warning time of Early Warning Signals. Also an attempt at removing window size uncertainty from EWS analysis

tomash-dev /Blood_Brain

This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.

prasannaghimiree /Breast-Cancer-Histopathology-Image-Segmentation-using-U-Net

Breast cancer histopathology image segmentation using U-Net. This repository implements U-Net for accurate segmentation of cancerous regions. It includes data augmentation, mixed precision training, checkpointing, and evaluation metrics like Dice score to improve model performance.

FANIMAN /healthcare-diagnosis-assistant---ml

A machine learning-based application designed to predict heart disease based on patient data. The project leverages the Heart Disease dataset from the UCI Machine Learning Repository, using various machine learning models to analyze and classify patient information for early disease detection.

SuryaVamsi-P /Diabetic-Retinopathy-Detection-with-ResNet50

Built an end-to-end deep learning pipeline using ResNet-50 to classify retinal images into five stages of Diabetic Retinopathy. Applied transfer learning, image preprocessing, and AUC-based evaluation on the APTOS 2019 Kaggle dataset, achieving a 94% validation AUC—offering real-world potential in clinical diagnosis automation.

Nirmala-research /YOLOv7-XAI

Multiclass Skin lesion localization and Detection with YOLOv7-XAI Framework with explainable AI

sfu-mial /DOTNet

Addresses the problem of reconstructing images acquired by diffuse optical tomography using deep learning.

Renu-code123 /Luna

AI-powered system for early detection of PCOS/PCOD risk and personalized lifestyle recommendations using machine learning and health data.