Frontiers

Semi-Supervised Learning with Foundation Models for Biomedical Data Analysis: Multimodality, Generative AI, and Clinical Adaptation

Biomedical data analysis has evolved rapidly from convolutional neural network-based systems toward transformer architectures and large-scale foundation ...
Frontiers

The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives

Grass-roots initiatives such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data- sharing Initiative (INDI) [1] are successfully amassing and sharing large-scale brain ...

Improving air temperature forecasts one to five weeks in advance without new model simulations

Researchers at the Institute of Industrial Science, The University of Tokyo and George Mason University's College of Science ...
IEEE

Machine Learning Models Tailored to Resource-Constrained Environments, with a Focus on Data Preprocessing Techniques

Abstract: In the era of pervasive computing, machine learning (ML) is increasingly deployed on resource-constrained devices, such as smartphones, IoT devices, and edge nodes. This research explores ML ...
Analytics Insight

10 Essential Exploratory Data Analysis Methods to Master in 2026

Overview: EDA techniques can help you translate your data into useful and actionable insights.Discover how top analysts uncover patterns, eliminate errors, and ...

The most innovative data science companies of 2026

Why Unstructured, Feedzai, Synchron, and Chalk are among Fast Company’s Most Innovative Companies in data science for 2026. AI innovations have long promised productivity at scale, powered by ...
IEEE

Data Driven Mental Health Predicting Depression Using Machine Learning

Abstract: The rise of information investigation methods such as machine learning is opening up unused openings in the field of mental wellbeing. This department of inquire about, known as data-driven ...