Breast Cancer Classification From Histopathological Images Using Patch-Based Deep Learning Modeling
Accurate detection and classification of breast cancer from histopathology images is critical but difficult due to the complexity of breast tissues.
Papers
1,138 of 1,138 verified cases.
Deep generative modeling for protein design
Designing novel proteins with desired structures, stability and function is slow and difficult; generative models are being applied to accelerate it.
Mining and Tailings Dam Detection in Satellite Imagery Using Deep Learning
Surface mines and mining tailings dams across Brazil, including unregistered ones, needed automatic identification from satellite imagery.
Machine learning-guided discovery and design of non-hemolytic peptides
Antimicrobial peptides are promising against antibiotic-resistant infections but their hemolytic toxicity blocks clinical use, and reliable computational prediction is hard.
Knowledge-driven drug repurposing using a comprehensive drug knowledge graph
New drug discovery and development is hugely expensive, so finding new uses for existing drugs is needed.
Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost
Predicting 30-day mortality in ICU sepsis-3 patients (MIMIC-III) early enough to guide treatment and improve survival.
Prediction of In‐hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data–Driven, Machine Learning Approach
Existing clinical decision rules for predicting in-hospital mortality in emergency department sepsis patients use few variables, generalize poorly, and cannot be easily updated.
Aboveground biomass estimation in a grassland ecosystem using Sentinel-2 satellite imagery and machine learning algorithms
Climate & Environment
Remote Sensing and LiDAR Applications
ai assisted
importance 7/10
scale stated
Aboveground biomass of grasslands must be estimated accurately to track carbon stocks and the carbon cycle.
Machine Learning for Structural Health Monitoring of Aerospace Structures: A Review
Engineering & Materials
Structural Health Monitoring Techniques
partially solved
importance 7/10
scale stated
Detecting, localizing, and predicting damage in aerospace structures from complex sensor data is critical for safety.
Peptide-based drug design using generative AI
Designing peptide-based drugs is slow and hindered by poor solubility, immunogenicity, toxicity and bioavailability.
Deep learning-based prediction of in-hospital mortality for sepsis
Existing clinical models for assessing mortality risk in sepsis patients rely on limited conventional indicators, leading to inaccurate risk assessment in the ICU.
METEO-DLNet: Quantitative Precipitation Nowcasting Net Based on Meteorological Features and Deep Learning
Climate & Environment
Precipitation Measurement and Analysis
ai assisted
importance 7/10
scale stated
Short-term precipitation forecasting via radar echo extrapolation struggles to account for inherent meteorological characteristics and local images that deviate from the overall trend.
Review of Methods for Automatic Plastic Detection in Water Areas Using Satellite Images and Machine Learning
Ocean plastic pollution forms growing 'rubbish islands' that damage marine ecosystems; sources, accumulation sites and movement need to be identified and tracked.
Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY® Sepsis, a prospective randomized clinical validation study
Sepsis in ICU patients is often detected too late, so clinicians need tools that predict its onset hours in advance.
Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects
Most genetic variants are non-coding and their effects on gene regulation are hard to interpret; deep learning tools have been developed to predict these effects.
Structure-based, deep-learning models for protein-ligand binding affinity prediction
Biology & Life Sciences
Computational Drug Discovery Methods
ai assisted
importance 7/10
scale stated
Predicting protein-ligand binding affinity from structure is a key open problem in computational drug discovery needing better methods.
An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery
Detecting wildfires quickly from satellite imagery so that response can limit damage to humans and wildlife.
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Engineering & Materials
Power System Optimization and Stability
ai assisted
importance 7/10
scale stated
Assessing the dynamic (transient) stability of modern power grids, whose structure and parameters change due to renewables and low inertia, in order to support emergency control.
Deep Learning-Based Attack Detection and Classification in Android Devices
Detecting and classifying malware attacks on Android devices, which dominate the global market, remains an ongoing challenge.
Weed Detection Using Deep Learning: A Systematic Literature Review
Weeds are harmful agricultural pests that raise production costs and damage the global agricultural economy, motivating early detection technology for farmers.
Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects
Medicine & Health
Medical Imaging Techniques and Applications
ai assisted
importance 7/10
scale stated
Standard filtered back projection CT reconstruction suffers from noise and artifacts at lower doses, while model-based iterative reconstruction is slow and yields unnatural image appearance.
Hybrid Surrogate Model for Timely Prediction of Flash Flood Inundation Maps Caused by Rapid River Overflow
Climate & Environment
Flood Risk Assessment and Management
partially solved
importance 7/10
scale stated
Physically based hydraulic models are too computationally slow to generate flash flood inundation maps in real time for urban early warning systems.
Tropical Cyclone Track Prediction with an Encoding-to-Forecasting Deep Learning Model
Climate & Environment
Tropical and Extratropical Cyclones Research
ai assisted
importance 7/10
scale stated
Predicting the tracks of tropical cyclones in the western North Pacific, where traditional dynamic and statistical methods struggle with efficiency and accuracy on large remote-sensing datasets.
Genomic Prediction of Wheat Grain Yield Using Machine Learning
Biology & Life Sciences
Genetic and phenotypic traits in livestock
ai assisted
importance 7/10
scale stated
Breeders need to predict wheat grain yield from genetic markers, but the best algorithms are unclear.