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View article: Navigating the tradeoff between personal privacy and data utility in speech anonymization for clinical research
Navigating the tradeoff between personal privacy and data utility in speech anonymization for clinical research Open
Speech data inherently contains personally identifiable information. Anonymization strategies to obscure this while preserving essential characteristics all represent a tradeoff between privacy and utility. We examine this balancing act of…
View article: Automating tumor-infiltrating lymphocyte assessment in breast cancer histopathology images using QuPath: a transparent and accessible machine learning pipeline
Automating tumor-infiltrating lymphocyte assessment in breast cancer histopathology images using QuPath: a transparent and accessible machine learning pipeline Open
In this study, we built an end-to-end tumor-infiltrating lymphocytes (TILs) assessment pipeline within QuPath, demonstrating the potential of easily accessible tools to perform complex tasks in a fully automatic fashion. First, we trained …
View article: Correction: “Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation”
Correction: “Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation” Open
[This corrects the article DOI: 10.2196/69820.].
View article: Open-source framework for detecting bias and overfitting for large pathology images
Open-source framework for detecting bias and overfitting for large pathology images Open
Even foundational models that are trained on datasets with billions of data samples may develop shortcuts that lead to overfitting and bias. Shortcuts are non-relevant patterns in data, such as the background color or color intensity. So, …
View article: A Lightweight and Extensible Cell Segmentation and Classification Model for Whole Slide Images
A Lightweight and Extensible Cell Segmentation and Classification Model for Whole Slide Images Open
Developing clinically useful cell-level analysis tools in digital pathology remains challenging due to limitations in dataset granularity, inconsistent annotations, high computational demands, and difficulties integrating new technologies …
View article: Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation
Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation Open
Background People with schizophrenia often present with cognitive impairments that may hinder their ability to learn about their condition. Education platforms powered by large language models (LLMs) have the potential to improve the acces…
View article: Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation (Preprint)
Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation (Preprint) Open
BACKGROUND People with schizophrenia often present with cognitive impairments that may hinder their ability to learn about their condition. Education platforms powered by large language models (LLMs) have the potential to improve the acce…
View article: Coding Historical Causes of Death Data with Large Language Models
Coding Historical Causes of Death Data with Large Language Models Open
This paper investigates the feasibility of using pre-trained generative Large Language Models (LLMs) to automate the assignment of ICD-10 codes to historical causes of death. Due to the complex narratives often found in historical causes o…
View article: Prompt Engineering a Schizophrenia Chatbot: Utilizing a Multi-Agent Approach for Enhanced Compliance with Prompt Instructions
Prompt Engineering a Schizophrenia Chatbot: Utilizing a Multi-Agent Approach for Enhanced Compliance with Prompt Instructions Open
Patients with schizophrenia often present with cognitive impairments that may hinder their ability to learn about their condition. These individuals could benefit greatly from education platforms that leverage the adaptability of Large Lan…
View article: Deep learning-based classification of breast cancer molecular subtypes from H&E whole-slide images
Deep learning-based classification of breast cancer molecular subtypes from H&E whole-slide images Open
Classifying breast cancer molecular subtypes is crucial for tailoring treatment strategies. While immunohistochemistry (IHC) and gene expression profiling are standard methods for molecular subtyping, IHC can be subjective, and gene profil…
View article: Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review
Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review Open
Aim In this review, we investigated how Machine Learning (ML) was utilized to predict all-cause somatic hospital admissions and readmissions in adults. Methods We searched eight databases (PubMed, Embase, Web of Science, CINAHL, ProQuest, …
View article: Social robots in research on social and cognitive development in infants and toddlers: A scoping review
Social robots in research on social and cognitive development in infants and toddlers: A scoping review Open
There is currently no systematic review of the growing body of literature on using social robots in early developmental research. Designing appropriate methods for early childhood research is crucial for broadening our understanding of you…
View article: Coding historical causes of death data with Large Language Models
Coding historical causes of death data with Large Language Models Open
This paper investigates the feasibility of using pre-trained generative Large Language Models (LLMs) to automate the assignment of ICD-10 codes to historical causes of death. Due to the complex narratives often found in historical causes o…
View article: Fast TILs -- A Pipeline for Efficient TILs Estimation in Non-Small Cell Lung Cancer
Fast TILs -- A Pipeline for Efficient TILs Estimation in Non-Small Cell Lung Cancer Open
Addressing the critical need for accurate prognostic biomarkers in cancer treatment, quantifying tumor-infiltrating lymphocytes (TILs) in non-small cell lung cancer (NSCLC) presents considerable challenges. Manual TIL quantification in who…
View article: More Efficient Manual Review of Automatically Transcribed Tabular Data
More Efficient Manual Review of Automatically Transcribed Tabular Data Open
Any machine learning method for transcribing historical text requires manual verification and correction, which is often time-consuming and expensive. Our aim is to make it more efficient. Previously, we developed a machine learning model …
View article: An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients
An individually adjusted approach for communicating epidemiological results on health and lifestyle to patients Open
If scientific research on modifiable risk factors was more accessible to the general population there is a potential to prevent disease and promote health. Mobile applications can automatically combine individual characteristics and statis…
View article: Social robots in research on social and cognitive development in infants and toddlers: A Scoping review
Social robots in research on social and cognitive development in infants and toddlers: A Scoping review Open
There is currently no systematic review of the growing body of literature on using social robots in early developmental research. Designing appropriate methods for early childhood research is crucial for broadening our understanding of you…
View article: Algorithm for predicting valvular heart disease from heart sounds in an unselected cohort
Algorithm for predicting valvular heart disease from heart sounds in an unselected cohort Open
Objective This study aims to assess the ability of state-of-the-art machine learning algorithms to detect valvular heart disease (VHD) from digital heart sound recordings in a general population that includes asymptomatic cases and interme…
View article: The Social Sunshine of the Arctic Youth: Exploring friendship’s influence on Vitamin D levels
The Social Sunshine of the Arctic Youth: Exploring friendship’s influence on Vitamin D levels Open
Background Vitamin D status correlates with 25OHD levels which depends on nutritional intake and UVB exposure. These two factors are influenced by friends, as people tend to participate in the same activities or eat a similar diet to their…
View article: Automated Coding of Historical Danish Cause of Death Data Using String Similarity
Automated Coding of Historical Danish Cause of Death Data Using String Similarity Open
The study of causes of death has been central to some of the most influential studies of the modern mortality decline in the nineteenth and twentieth centuries. The digitization of individual-level cause of-death data has been game-changin…
View article: Ethical Challenges of Using Synthetic Data
Ethical Challenges of Using Synthetic Data Open
There is an outburst of digitized medical data with the growing adoption of Electronic Health Record (EHR) systems but have restricted access due to legal compliances. This lack of data accessibility has piqued the interest in generating a…
View article: From research to clinic: Accelerating the translation of clinical decision support systems by making synthetic data interoperable
From research to clinic: Accelerating the translation of clinical decision support systems by making synthetic data interoperable Open
The translation of clinical decision support system (CDSS) tools from research settings into the clinic is often non-existent, partly because the focus tends to be on training machine learning models rather than tool development using the …
View article: More efficient manual review of automatically transcribed tabular data
More efficient manual review of automatically transcribed tabular data Open
Machine learning methods have proven useful in transcribing historical data. However, results from even highly accurate methods require manual verification and correction. Such manual review can be time-consuming and expensive, therefore t…
View article: Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review
Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review Open
Advancements in digital pathology and computing resources have made a significant impact in the field of computational pathology for breast cancer diagnosis and treatment. However, access to high-quality labeled histopathological images of…
View article: Simplifying and personalising health information with mobile apps: translating complex models into understandable visuals
Simplifying and personalising health information with mobile apps: translating complex models into understandable visuals Open
Background If patients could utilise scientific research about modifiable risk factors there is a potential to prevent disease and promote health. Mobile applications can automatically adjust what and how information is presented based on …
View article: Algorithm for Predicting Valvular Heart Disease from Heart Sounds in an Unselected Cohort
Algorithm for Predicting Valvular Heart Disease from Heart Sounds in an Unselected Cohort Open
Background Although neural networks have shown promise in classifying pathological heart sounds (HS), algorithms have so far either been trained or tested on selected cohorts which can result in selection bias. Herein, the main objective i…