HackerNoon

Three AI Agents Held a Conference and Decided I Should Do the Work Instead

Three AI agents built competing model recommenders, audited one another, and concluded that human judgment was still ...
BMJ

Predicting cardiovascular events from routine mammograms using machine learning

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...
ahajournals.org

Phenotypic Selectivity of Artificial Intelligence–Enhanced Electrocardiography in Cardiovascular Diagnosis and Risk Prediction

Artificial intelligence (AI)–enhanced ECG (AI-ECG) models are often designed to detect specific anatomical and functional cardiac abnormalities. Understanding the selectivity of their phenotypic ...
GitHub

TIP: Tabular-Image Pre-training for Multimodal Classification with Incomplete Data (ECCV 2024)

Model architecture and algorithm of TIP: (a) Model overview with its image encoder, tabular encoder, and multimodal interaction module, which are pre-trained using 3 SSL losses: $\mathcal{L}_{itc}$, $ ...
C&EN

Meta Learning with Attention Based FP-GNNs for Few-Shot Molecular Property Prediction

Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Bioinformatics Department, School of ...
Visual Studio Magazine

Multi-Class Classification Using LightGBM

Dr. James McCaffrey of Microsoft Research provides a full-code, step-by-step machine learning tutorial on how to use the LightGBM system to perform multi-class classification using Python and the ...
InfoWorld

What is TensorFlow? The machine learning library explained

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...
Frontiers

Convolutional Neural Network for Skin Lesion Classification: Understanding the Fundamentals Through Hands-On Learning

Deep learning architectures for the classification of images have shown outstanding results in a variety of disciplines, including dermatology. The expectations generated by deep learning for, e.g., ...
Frontiers

Machine Learning Techniques for Soybean Charcoal Rot Disease Prediction

Early prediction of pathogen infestation is a key factor to reduce the disease spread in plants. Macrophomina phaseolina (Tassi) Goid, as one of the main causes of charcoal rot disease, suppresses the ...
Visual Studio Magazine

Binary Classification Using PyTorch: Training

Dr. James McCaffrey of Microsoft Research continues his examination of creating a PyTorch neural network binary classifier through six steps, here addressing step No. 4: training the network. The goal ...