A5083904567- Ruminant Nutrition and Digestive Physiology
- Genetic and phenotypic traits in livestock
- Livestock Management and Performance Improvement
- Crop Yield and Soil Fertility
- Rabbits: Nutrition, Reproduction, Health
- Food composition and properties
- Nitrogen and Sulfur Effects on Brassica
- Artificial Intelligence in Healthcare and Education
- Reproductive Physiology in Livestock
- Research in Cotton Cultivation
- Topic Modeling
- Genetically Modified Organisms Research
- Agronomic Practices and Intercropping Systems
- Insect Resistance and Genetics
- Peanut Plant Research Studies
- Liver Disease Diagnosis and Treatment
- Machine Learning in Healthcare
- Genomics, phytochemicals, and oxidative stress
- Animal Nutrition and Physiology
- Fatty Acid Research and Health
- Natural Products and Biological Research
- Biofuel production and bioconversion
- Agriculture, Soil, Plant Science
- Animal Genetics and Reproduction
- Radiology practices and education
Google (United States)
2024-2025
Google (United Kingdom)
2024
National Dairy Research Institute
2001-2016
Navsari Agricultural University
2012
BackgroundMedicine is inherently multimodal, requiring the simultaneous interpretation and integration of insights between many data modalities spanning text, imaging, genomics, more. Generalist biomedical artificial intelligence systems that flexibly encode, integrate, interpret these might better enable impactful applications ranging from scientific discovery to care delivery.MethodsTo catalyze development models, we curated MultiMedBench, a new multimodal benchmark. MultiMedBench...
Large language models (LLMs) have shown promise in medical question answering, with Med-PaLM being the first to exceed a 'passing' score United States Medical Licensing Examination style questions. However, challenges remain long-form answering and handling real-world workflows. Here, we present 2, which bridges these gaps combination of base LLM improvements, domain fine-tuning new strategies for improving reasoning grounding through ensemble refinement chain retrieval. 2 scores up 86.5% on...
Automated radiology report generation has the potential to improve patient care and reduce workload of radiologists. However, path toward real-world adoption been stymied by challenge evaluating clinical quality artificial intelligence (AI)-generated reports. We build a state-of-the-art system for chest radiographs, called Flamingo-CXR, perform an expert evaluation AI-generated reports engaging panel board-certified observe wide distribution preferences across settings, with 56.1%...
Abstract At the heart of medicine lies physician–patient dialogue, where skillful history-taking enables effective diagnosis, management and enduring trust 1,2 . Artificial intelligence (AI) systems capable diagnostic dialogue could increase accessibility quality care. However, approximating clinicians’ expertise is an outstanding challenge. Here we introduce AMIE (Articulate Medical Intelligence Explorer), a large language model (LLM)-based AI system optimized for dialogue. uses...
Abstract A comprehensive differential diagnosis is a cornerstone of medical care that often reached through an iterative process interpretation combines clinical history, physical examination, investigations and procedures. Interactive interfaces powered by large language models present new opportunities to assist automate aspects this 1 . Here we introduce the Articulate Medical Intelligence Explorer (AMIE), model optimized for diagnostic reasoning, evaluate its ability generate alone or as...
<title>Abstract</title> Radiology reports are an instrumental part of modern medicine, informing key clinical decisions such as diagnosis and treatment. The worldwide shortage radiologists, however, restricts access to expert care imposes heavy workloads, contributing avoidable errors in report delivery. While recent progress automated generation with vision-language models offers clear potential ameliorate this situation, the path toward real-world adoption has been stymied by challenge...
Twenty crossbred lactating multiparous cows were used in a 28-day study to compare dry matter intake (DMI), milk yield, composition and Bacillus thuringiensis (Bt) protein concentrations plasma when fed diets containing Bollgard II(®) cottonseed (BGII) or control non-genetically modified isogenic (CON). II contains the Cry1Ac Cry2Ab insecticidal proteins that protect cotton plants from feeding damage caused by certain lepidopteran insects. Cows assigned randomly BGII CON treatments after...