Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information
R Hamamoto, T Koyama, N Kouno, T Yasuda… - … hematology & oncology, 2022 - Springer
Abstract Since US President Barack Obama announced the Precision Medicine Initiative in
his New Year's State of the Union address in 2015, the establishment of a precision …
his New Year's State of the Union address in 2015, the establishment of a precision …
The research landscape on generative artificial intelligence: a bibliometric analysis of transformer-based models
G Marchena Sekli - Kybernetes, 2024 - emerald.com
Purpose The aim of this study is to offer valuable insights to businesses and facilitate better
understanding on transformer-based models (TBMs), which are among the widely employed …
understanding on transformer-based models (TBMs), which are among the widely employed …
Adverse event signal extraction from cancer patients' narratives focusing on impact on their daily-life activities
Adverse event (AE) management is important to improve anti-cancer treatment outcomes,
but it is known that some AE signals can be missed during clinical visits. In particular, AEs …
but it is known that some AE signals can be missed during clinical visits. In particular, AEs …
[HTML][HTML] Adverse Event Signal Detection Using Patients' Concerns in Pharmaceutical Care Records: Evaluation of Deep Learning Models
S Nishioka, S Watabe, Y Yanagisawa… - Journal of medical …, 2024 - jmir.org
Background Early detection of adverse events and their management are crucial to
improving anticancer treatment outcomes, and listening to patients' subjective opinions …
improving anticancer treatment outcomes, and listening to patients' subjective opinions …
Exploring a method for extracting concerns of multiple breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation …
Narratives posted on the internet by patients contain a vast amount of information about
various concerns. This study aimed to extract multiple concerns from interviews with breast …
various concerns. This study aimed to extract multiple concerns from interviews with breast …
[HTML][HTML] Differing Content and Language Based on Poster-Patient Relationships on the Chinese Social Media Platform Weibo: Text Classification, Sentiment Analysis …
Background: Breast cancer affects the lives of not only those diagnosed but also the people
around them. Many of those affected share their experiences on social media. However …
around them. Many of those affected share their experiences on social media. However …
A systematic review of application progress on machine learning-based natural language processing in breast cancer over the past 5 years
Artificial intelligence (AI) has been steadily developing in the medical field in the past few
years, and AI-based applications have advanced cancer diagnosis. Breast cancer has a …
years, and AI-based applications have advanced cancer diagnosis. Breast cancer has a …
Symptom-BERT: Enhancing Cancer Symptom Detection in EHR Clinical Notes
Context Extracting cancer symptom documentation allows clinicians to develop highly
individualized symptom prediction algorithms to deliver symptom management care …
individualized symptom prediction algorithms to deliver symptom management care …
A study of Rwanda's two-way text messaging support for isolated COVID-19 patients during the pandemic: patient use and AI-enhanced conversation analysis
MA Manson - 2024 - open.library.ubc.ca
Background: In Rwanda, a two-way-SMS-based mHealth intervention, WelTel, was
deployed to support isolated COVID-19 patients throughout the pandemic. Patients received …
deployed to support isolated COVID-19 patients throughout the pandemic. Patients received …