AIMC Topic: Text Messaging

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Application of AI Chatbot in Responding to Asynchronous Text-Based Messages From Patients With Cancer: Comparative Study.

Journal of medical Internet research May 21, 2025
BACKGROUND: Telemedicine, which incorporates artificial intelligence such as chatbots, offers significant potential for enhancing health care delivery. However, the efficacy of artificial intelligence chatbots compared to human physicians in clinical...
Physician-Patient Relations Patient Education as Topic Telemedicine China Generative Artificial Intelligence Text Messaging Aged Adult Middle Aged Neoplasms Humans Male Artificial Intelligence Female
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Building and Beta-Testing Be Well Buddy Chatbot, a Secure, Credible and Trustworthy AI Chatbot That Will Not Misinform, Hallucinate or Stigmatize Substance Use Disorder: Development and Usability Study.

JMIR human factors May 7, 2025
BACKGROUND: Artificially intelligent (AI) chatbots that deploy natural language processing and machine learning are becoming more common in health care to facilitate patient education and outreach; however, generative chatbots such as ChatGPT face ch...
Computer Security Texas Text Messaging Machine Learning Generative Artificial Intelligence Substance-Related Disorders Humans Artificial Intelligence
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Development and evaluation of a 4M taxonomy from nursing home staff text messages using a fine-tuned generative language model.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2025
OBJECTIVE: This study aimed to explore the utilization of a fine-tuned language model to extract expressions related to the Age-Friendly Health Systems 4M Framework (What Matters, Medication, Mentation, and Mobility) from nursing home worker text mes...
Humans Natural Language Processing Nursing Homes Text Messaging Missouri
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Analysing common topics of secure patient messages in hidradenitis suppurativa: a text-embedding and natural language-processing approach.

The British journal of dermatology Sep 18, 2024
Humans Natural Language Processing Text Messaging Hidradenitis Suppurativa
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Using large language model to guide patients to create efficient and comprehensive clinical care message.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2024
OBJECTIVE: This study aims to investigate the feasibility of using Large Language Models (LLMs) to engage with patients at the time they are drafting a question to their healthcare providers, and generate pertinent follow-up questions that the patien...
Text Messaging Physician-Patient Relations Feasibility Studies Humans Artificial Intelligence
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Towards Optimizing LLM Use in Healthcare: Identifying Patient Questions in MyChart Messages.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
The volume of patient-provider messages is on the rise, and Large Language Models (LLMs) can potentially streamline the clinical messaging process, but their success hinges on triaging messages they can optimally address. In this study, we analyzed E...
Electronic Health Records Natural Language Processing Text Messaging Humans
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Designing Depression Screening Chatbots.

Studies in health technology and informatics Dec 15, 2021
Advances in voice recognition, natural language processing, and artificial intelligence have led to the increasing availability and use of conversational agents (chatbots) in different settings. Chatbots are systems that mimic human dialogue interact...
Communication Depression Text Messaging Artificial Intelligence Delivery of Health Care Humans
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A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

Critical care medicine Nov 1, 2019
OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.
Hospitals, Teaching Decision Support Systems, Clinical Shock, Septic Text Messaging Sepsis Cohort Studies Humans Machine Learning Electronic Health Records Sensitivity and Specificity Diagnosis, Computer-Assisted Algorithms Retrospective Studies
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Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Critical care medicine Nov 1, 2019
OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0).
Practice Patterns, Nurses' Hospitals, Teaching Humans Algorithms Prospective Studies Machine Learning Shock, Septic Practice Patterns, Physicians' Nursing Staff, Hospital Attitude of Health Personnel Medical Staff, Hospital Text Messaging Sepsis Decision Support Systems, Clinical Electronic Health Records Diagnosis, Computer-Assisted
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Acid-Base Reports Need a Text Explanation.

Anesthesiology Apr 1, 2019
Acid-Base Equilibrium Research Report Text Messaging Humans Artificial Intelligence
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