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GraphKM: machine and deep learning for K prediction of wildtype and mutant enzymes.

BMC bioinformatics
Michaelis constant (K) is one of essential parameters for enzymes kinetics in the fields of protein engineering, enzyme engineering, and synthetic biology. As overwhelming experimental measurements of K are difficult and time-consuming, prediction of...

A deep learning approach for Named Entity Recognition in Urdu language.

PloS one
Named Entity Recognition (NER) is a natural language processing task that has been widely explored for different languages in the recent decade but is still an under-researched area for the Urdu language due to its rich morphology and language comple...

Layerwised multimodal knowledge distillation for vision-language pretrained model.

Neural networks : the official journal of the International Neural Network Society
The transformer-based model can simultaneously learn the representation for both images and text, providing excellent performance for multimodal applications. Practically, the large scale of parameters may hinder its deployment in resource-constraine...

Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.

Journal of biomedical informatics
OBJECTIVE: Acknowledging study limitations in a scientific publication is a crucial element in scientific transparency and progress. However, limitation reporting is often inadequate. Natural language processing (NLP) methods could support automated ...

Artificial intelligence large language model ChatGPT: is it a trustworthy and reliable source of information for sarcoma patients?

Frontiers in public health
INTRODUCTION: Since its introduction in November 2022, the artificial intelligence large language model ChatGPT has taken the world by storm. Among other applications it can be used by patients as a source of information on diseases and their treatme...

Current safeguards, risk mitigation, and transparency measures of large language models against the generation of health disinformation: repeated cross sectional analysis.

BMJ (Clinical research ed.)
OBJECTIVES: To evaluate the effectiveness of safeguards to prevent large language models (LLMs) from being misused to generate health disinformation, and to evaluate the transparency of artificial intelligence (AI) developers regarding their risk mit...

Screening/diagnosis of pediatric endocrine disorders through the artificial intelligence model in different language settings.

European journal of pediatrics
UNLABELLED: This study is aimed at examining the impact of ChatGPT on pediatric endocrine and metabolic conditions, particularly in the areas of screening and diagnosis, in both Chinese and English modes. A 40-question questionnaire covering the four...

STELA: a community-centred approach to norm elicitation for AI alignment.

Scientific reports
Value alignment, the process of ensuring that artificial intelligence (AI) systems are aligned with human values and goals, is a critical issue in AI research. Existing scholarship has mainly studied how to encode moral values into agents to guide th...

A visual-language foundation model for computational pathology.

Nature medicine
The accelerated adoption of digital pathology and advances in deep learning have enabled the development of robust models for various pathology tasks across a diverse array of diseases and patient cohorts. However, model training is often difficult d...

Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping review.

Journal of educational evaluation for health professions
BACKGROUND: ChatGPT is a large language model (LLM) based on artificial intelligence (AI) capable of responding in multiple languages and generating nuanced and highly complex responses. While ChatGPT holds promising applications in medical education...