Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data scientists should master both supervised ...

Overview: Building AI models begins with clear goals, clean data, and selecting appropriate algorithms.Beginners can use tools like Python, scikit-learn, and Te ...

A new study finds that many popular image datasets used to train AI models are contaminated with test images or ...

What if plants could speak when they were thirsty? Agriculture, in essence, is a dialog among crops, soil and climate. Yet drought, the most insidious stressor, remains largely silent until its damage ...

In the Age of AI, many health care providers dream of a digital assistant, unencumbered by fatigue, workload, burnout or ...

New model extracts stiffness and fluidity from AFM data in minutes, enabling fast, accurate mechanical characterization of ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Artificial intelligence is accelerating material discovery and design by automating analysis, guiding experiments, and enabling predictive modeling across spectroscopy, microscopy, and synthesis.

Efficiency in AI development, paired with open source sharing in the industry, can help empower startups and enterprise ML teams to compete with tech giants. Instead of wasting budget and human time ...