The ‘AgriHub,’ Innovation Hub for Agriculture at the Indian Institute of Technology Indore, is emerging as a major centre for AI-based agricultural innovation in India. Inaugurated on January 27, 2025 ...

Cellar Insights deploys potato storage technology using wireless sensors and machine learning to cut post-harvest losses for ...

Abstract: Massive challenges in agriculture such as crop diseases, improper fertilizer usage, and unsuitable crop selection lead to significant productivity and economic losses for farmers. This study ...

Open-source AI agriculture platform — TensorFlow crop yield prediction, OpenCV plant disease detection, JWT-authenticated Flask REST API, SQLite crop marketplace, and a React 18 + Vite dashboard. Self ...

Farmers have long fought a quiet war against the fungi that rot crops in fields and storage sheds. Each year, these diseases destroy harvests of lettuce, beans, oilseed rape, wheat, and many other ...

Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...

Crop Disease Detection using Machine Learning is a CNN-based system that identifies crop diseases from leaf images and provides preventive measures, helping farmers detect diseases early and reduce ...

Baseline biomarker analysis and clinical outcomes of the PD-1/TGFβR2 bispecific antibody INCA33890 in patients with non-MSI-H metastatic colorectal cancer (mCRC). This is an ASCO Meeting Abstract from ...

Coupling tumor genomics, whole transcriptome sequencing, and patient outcomes to define the tumor microenvironment in receptor tyrosine amplified gastrointestinal cancers: Analysis from 24,598 cases.

Abstract: Artificial Intelligence (AI) has become a vital tool for agricultural farming. AI-based image processing models utilizing different machine learning (ML) algorithms and deep learning (DL) ...

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant measurements and environmental data. By training models on seven years of ...