A GUI based on napari for counting cells automatically in cell migration experiments

OOD Dataset Curator and Benchmark for AI-aided Drug Discovery

Predicting tandem mass spectra from molecules

Efficiently predicting high resolution mass spectra with graph neural networks

Chemcrow

[Bioinformatics] 3DMolMS: prediction of tandem mass spectra from 3D molecular conformations

A global network optimization approach for untargeted LC-MS metabolomics data annotation and metabolite discovery

Image-based trace signal detection from Mass Spectrometry with machine learning

Data analysis for single-lysosome mass spectrometry

Bayesian optimization of LC gradient for untargeted chemical analysis

Accurately estimate FDR in metabolomics using entropy-based decoy methods.

A Deep Learning Framework to Interpret Raw Mass Spectrometry (m/z) Data

The official sources for the RDKit library

MSBooster allows users to add deep learning-based features to .pin files before Percolator PSM rescoring

Mass Spectrometry for Small Molecules using Deep Learning

Bottom-up MS/MS interrogation & Experiment-specific global annotation

python-lekin: Flexible Supply Chain Planning and Scheduler

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

Prototypical multiple instance learning for predicting lymph node metastasis of breast cancer from whole-slide pathological images

Attention Based Deep 3D Multiple Instance Learning

This is a reimplementation of AG-CNN. ("Thorax Disease Classification with Attention Guided Convolutional Neural Network","Diagnose like a Radiologist: Attention Guided Convolutional Neural Network…

Official code for Breast Cancer Histopathology Image Classification and Localization using Multiple Instance Learning

Implementation of region growing algorithm for liver extraction in CT/MRI scans.

An end to end automatic segmentation tool for MRI files, that can identify lungs, bladder, liver, kidney and bone

Repo for handing off MRE projects

Multi-instance deep learning of ultrasound imaging data for pattern classification of congenital abnormalities of the kidney and urinary tract in children