There are 6 repositories under clinical topic.
An electronic data capture platform for administering remote and in-person clinical instruments
Medkey Hospital Information System main repository: Practice Management for Practicioners & Hospitals, EHR, Patient Engagement
Mutation Identification Pipeline. Read the latest documentation:
A reported 96,480 people were diagnosed with melanoma in the United States in 2019, leading to 7230 reported deaths. Early-stage identification of suspicious pigmented lesions (SPLs) in primary care settings can lead to im- proved melanoma prognosis and a possible 20-fold reduction in treatment cost. Despite this clinical and economic value, efficient tools for SPL detection are mostly absent. To bridge this gap, we developed an SPL analysis system for wide-field images using deep convolutional neural networks (DCNNs) and applied it to a 38,283 dermatological dataset collected from 133 patients and publicly available images. These images were obtained from a variety of consumer-grade cameras (15,244 nondermoscopy) and classified by three board-certified dermatologists. Our system achieved more than 90.3% sensitivity (95% confidence interval, 90 to 90.6) and 89.9% specificity (89.6 to 90.2%) in distinguishing SPLs from nonsuspicious lesions, skin, and complex backgrounds, avoiding the need for cumbersome individual lesion imaging. We also present a new method to extract intrapatient lesion saliency (ugly duckling criteria) on the basis of DCNN features from detected lesions. This saliency ranking was validated against three board-certified dermatologists using a set of 135 individual wide-field images from 68 dermatolog- ical patients not included in the DCNN training set, exhibiting 82.96% (67.88 to 88.26%) agreement with at least one of the top three lesions in the dermatological consensus ranking. This method could allow for rapid and accurate assessments of pigmented lesion suspiciousness within a primary care visit and could enable improved patient triaging, utilization of resources, and earlier treatment of melanoma.
Integrating AI to Clinical Workflow
Official source for Spanish pretrained biomedical and clinical language models and resources made @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).
Community-maintained list of resources that the CI4CC organization and the larger cancer informatics community have found useful or are developing.
Reconstruction and analysis of viral and host genomes at multi-organ level
Metagenomics/viromics pipeline that focuses on automation, user-friendliness and a clear audit trail. Jovian aims to empower classical biologists and wet-lab personnel to do metagenomics/viromics analyses themselves, without bioinformatics expertise.
This project develops compact transformer models tailored for clinical text analysis, balancing efficiency and performance for healthcare NLP tasks.
Seave is a web platform that enables genetic variants to be easily filtered and annotated with in silico pathogenicity prediction scores and annotations from popular disease databases. Seave stores genomic variation of all types and sizes, and allows filtering for specific inheritance patterns, quality values, allele frequencies and gene lists. Seave is open source and deployable locally, or on a cloud computing provider, and works readily with gene panel, exome and whole genome data, scaling from single labs to multi-institution scale.
A fine-tuned BERT using EHR notes.
C++ implementation of several image contrast enhancement techniques for clinical and normal images.
A project to develop a realistic XR Virtual Environment using Gaussian Splatting and Unreal Engine.
A Java application designed to streamline the management of clinics offering dental and orthodontic services. This project, developed using Java Swing, provides essential tools for such clinics, making it ideal for single-doctor practices. It helps manage patients, appointments, records and more.
Bacterial typing pipeline for clinical NGS data. Written in NextFlow, Python & Bash.
Integrated tool to build efficiently a genetic pedigree, a boadicea file and generate the corresponding clinical story [english/french]. Outil intégré pour construire efficacement un pedigree génétique, un fichier boadicea et générer l'histoire clinique correspondante. Disponible en français et en anglais.
Healthcare and biomedical datasets, for AI/ML
Improving clinical pathways in an open source and modular fashion
PyTorch library for MIMIC III Benchmark experiments