Behind the Paper
The real stories behind the latest research papers, from conception to publication, the highs and the lows
Filtered by: General & Internal Medicine
Deep learning-based microsatellite instability predictor from prostate cancer whole-slide images
Researchers developed a deep learning predictor of MSI in prostate cancer using a large, real-world cohort of H&E whole slide images. The screening algorithm may be used to rapidly prioritize patients for confirmatory testing, which can identify MSI-high patients who may qualify for immunotherapy.
The UK Clinical Eye Research Strategy Unveils New Priorities
The UK Clinical Eye Research Strategy has embarked on a transformative journey to update and refine research priorities in ophthalmology. We delve into the key findings and implications of this groundbreaking initiative, aimed at reshaping the landscape of eye research in the United Kingdom.
The Role of Smartwatch Data in Monitoring Non-Motor Symptoms of Parkinson’s Disease
Accurate and continuous monitoring of symptoms can enable better care and timely intervention. Wearables could facilitate this but are underexplored for monitoring of non-motor symptoms.
Behind the paper: Unraveling the molecular mechanism behind COVID-19 pulmonary pathologies associated with ferroptosis
How we found that ferroptosis is a key driver of lung damage in severe COVID-19 patients,
By Baiyu Qiu, Fereshteh Zandkarimi, Anjali Saqi and Brent R. Stockwell
Essential Fatty Acids: A Potential Solution for Post-COVID-19 Long-Haul Manifestations
This blog was written by Undurti N. Das. Prof. Das is a clinical immunologist, endocrinologist and the founder president and chief executive officer of UND Life Sciences.
Smart Clinics in Ophthalmology: Automatic Fundus Fluorescein Angiography Image Interpretation with Large Language Models
FFA-GPT is an automated system for ophthalmic image interpretation that enables both report generation and interactive question answering for fundus fluorescein angiography images.
Intrapartum Ultrasound Image Analysis: Beginning from Standard Planes
PSFHSP-Net: an efficient lightweight network for identifying pubic symphysis-fetal head standard plane from intrapartum ultrasound images (avaliable at https://github.com/Yaucleo/HPSSPNet).
