AIMC Topic: Natural Language Processing

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Predicting patients' sentiments about medications using artificial intelligence techniques.

Scientific reports
The increasing development of technology has led to the increase of digital data in various fields, such as medication-related texts. Sentiment Analysis (SA) in medication is essential to give clinicians insights into patients' feedback about the tre...

Use of large language models as artificial intelligence tools in academic research and publishing among global clinical researchers.

Scientific reports
With breakthroughs in Natural Language Processing and Artificial Intelligence (AI), the usage of Large Language Models (LLMs) in academic research has increased tremendously. Models such as Generative Pre-trained Transformer (GPT) are used by researc...

Deep neural networks and humans both benefit from compositional language structure.

Nature communications
Deep neural networks drive the success of natural language processing. A fundamental property of language is its compositional structure, allowing humans to systematically produce forms for new meanings. For humans, languages with more compositional ...

The Utilization of Natural Language Processing for Analyzing Social Media Data in Nursing Research: A Scoping Review.

Journal of nursing management
This scoping review aimed to identify and synthesize the evidence in existing nursing studies that used natural language processing to analyze social media data, and the relevant procedures, techniques, tools, and ethical issues. Social media has w...

Ascertaining provider-level implicit bias in electronic health records with rules-based natural language processing: A pilot study in the case of prostate cancer.

PloS one
PURPOSE: Implicit, unconscious biases in medicine are personal attitudes about race, ethnicity, gender, and other characteristics that may lead to discriminatory patterns of care. However, there is no consensus on whether implicit bias represents a t...

The aluminum standard: using generative Artificial Intelligence tools to synthesize and annotate non-structured patient data.

BMC medical informatics and decision making
BACKGROUND: Medical narratives are fundamental to the correct identification of a patient's health condition. This is not only because it describes the patient's situation. It also contains relevant information about the patient's context and health ...

Porter 6: Protein Secondary Structure Prediction by Leveraging Pre-Trained Language Models (PLMs).

International journal of molecular sciences
Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein f...

Artificial Intelligence (AI) and Men's Health Clinic Efficiency and Clinic Billing.

Current urology reports
PURPOSE OF REVIEW: Artificial Intelligence (AI) has produced a significant impact across various industries, including healthcare. In the outpatient clinic setting, AI offers promising improvements in efficiency through Chatbots, streamlined medical ...

Identifying technologies in circular economy paradigm through text mining on scientific literature.

PloS one
Technological innovation serves as the catalyst for the shift towards circular practices. Technologies not only address technical challenges, facilitating the transition to a more circular economy, but they also enhance business efficiency and profit...

Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation.

SLAS technology
This study delves into the transformative potential of Machine Learning (ML) and Natural Language Processing (NLP) within the pharmaceutical industry, spotlighting their significant impact on enhancing medical research methodologies and optimizing he...