The Many Hosts of Mycobacteria 9 (MHM9): A conference report
Abstract The Many Hosts of Mycobacteria (MHM) meeting series brings together basic
scientists, clinicians and veterinarians to promote robust discussion and dissemination of …
scientists, clinicians and veterinarians to promote robust discussion and dissemination of …
[HTML][HTML] Attention2majority: Weak multiple instance learning for regenerative kidney grading on whole slide images
Deep learning consistently demonstrates high performance in classifying and segmenting
medical images like CT, PET, and MRI. However, compared to these kinds of images, whole …
medical images like CT, PET, and MRI. However, compared to these kinds of images, whole …
Deep weakly-supervised learning methods for classification and localization in histology images: a survey
Using deep learning models to diagnose cancer from histology data presents several
challenges. Cancer grading and localization of regions of interest (ROIs) in these images …
challenges. Cancer grading and localization of regions of interest (ROIs) in these images …
Contrastive multiple instance learning: An unsupervised framework for learning slide-level representations of whole slide histopathology images without labels
Simple Summary Recent AI methods in the automated analysis of histopathological imaging
data associated with cancer have trended towards less supervision by humans. Yet, there …
data associated with cancer have trended towards less supervision by humans. Yet, there …
Immunological roads diverged: mapping tuberculosis outcomes in mice
RK Meade, CM Smith - Trends in Microbiology, 2024 - cell.com
The journey from phenotypic observation to causal genetic mechanism is a long and
challenging road. For pathogens like Mycobacterium tuberculosis (Mtb), which causes …
challenging road. For pathogens like Mycobacterium tuberculosis (Mtb), which causes …
CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice
D Koyuncu, MKK Niazi, T Tavolara, C Abeijon… - PLoS …, 2021 - journals.plos.org
More humans have died of tuberculosis (TB) than any other infectious disease and millions
still die each year. Experts advocate for blood-based, serum protein biomarkers to help …
still die each year. Experts advocate for blood-based, serum protein biomarkers to help …
BCR-Net: A deep learning framework to predict breast cancer recurrence from histopathology images
Breast cancer is the most common malignancy in women, with over 40,000 deaths annually
in the United States alone. Clinicians often rely on the breast cancer recurrence score …
in the United States alone. Clinicians often rely on the breast cancer recurrence score …
Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in Mycobacterium tuberculosis infected Diversity Outbred …
Background Machine learning sustains successful application to many diagnostic and
prognostic problems in computational histopathology. Yet, few efforts have been made to …
prognostic problems in computational histopathology. Yet, few efforts have been made to …
Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice
DM Gatti, AL Tyler, JM Mahoney, GA Churchill… - PLoS …, 2024 - journals.plos.org
Mycobacterium tuberculosis infects two billion people across the globe, and results in 8–9
million new tuberculosis (TB) cases and 1–1.5 million deaths each year. Most patients have …
million new tuberculosis (TB) cases and 1–1.5 million deaths each year. Most patients have …
Prediction of Tuberculosis From Lung Tissue Images of Diversity Outbred Mice Using Jump Knowledge Based Cell Graph Neural Network
Tuberculosis (TB), primarily affecting the lungs, is caused by the bacterium Mycobacterium
tuberculosis and poses a significant health risk. Detecting acid-fast bacilli (AFB) in stained …
tuberculosis and poses a significant health risk. Detecting acid-fast bacilli (AFB) in stained …