Melissa D McCradden
Dados Biográficos
| ID | 5413151 |
|---|---|
| NOME | Melissa D McCradden |
| PRENOMES | Melissa D |
| SOBRENOME | McCradden |
| ASSINATURA | MCCRADDEN M D |
| AFILIAÇÕES | University of Toronto |
| ORCID | 0000-0002-6476-2165 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 7 |
| TOTAL DE CITAÇÕES | 3 |
| TOTAL COMO AUTOR | 7 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2019 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 1 |
“There's more to recovery than just weight gain”
Machine learning used to study risk factors for chronic diseases
OBJECTIVES: Machine learning (ML) has received significant attention for its potential to process and learn from vast amounts of data. Our aim was to perform a scoping review to identify studies that used ML to study risk factors for chronic diseases at a population level, notably those that incorporated methods to mitigate algorithmic bias. We focused on ML applications for the most common risk factors for chronic disease: tobacco use, alcohol u…
Digital tools for youth health promotion
Although digital health promotion (DHP) technologies for young people are increasingly available in low- and middle-income countries (LMICs), there has been insufficient research investigating whether existing ethical and policy frameworks are adequate to address the challenges and promote the technological opportunities in these settings. In an effort to fill this gap and as part of a larger research project, in November 2022, we conducted a wor…
Exploring potential barriers in equitable access to pediatric diagnostic imaging using machine learning
In this work, we examine magnetic resonance imaging (MRI) and ultrasound (US) appointments at the Diagnostic Imaging (DI) department of a pediatric hospital to discover possible relationships between selected patient features and no-show or long waiting room time endpoints. The chosen features include age, sex, income, distance from the hospital, percentage of non-English speakers in a postal code, percentage of single caregivers in a postal code…
Evidence, ethics and the promise of artificial intelligence in psychiatry
Researchers are studying how artificial intelligence (AI) can be used to better detect, prognosticate and subgroup diseases. The idea that AI might advance medicine’s understanding of biological categories of psychiatric disorders, as well as provide better treatments, is appealing given the historical challenges with prediction, diagnosis and treatment in psychiatry. Given the power of AI to analyse vast amounts of information, some clinicians m…
Ambiguous identities of drugs and people
Staying true to Rowan’s Law
Ambiguous identities of drugs and people
Staying true to Rowan’s Law
Exploring potential barriers in equitable access to pediatric diagnostic imaging using machine learning
In this work, we examine magnetic resonance imaging (MRI) and ultrasound (US) appointments at the Diagnostic Imaging (DI) department of a pediatric hospital to discover possible relationships between selected patient features and no-show or long waiting room time endpoints. The chosen features include age, sex, income, distance from the hospital, percentage of non-English speakers in a postal code, percentage of single caregivers in a postal code…
Evidence, ethics and the promise of artificial intelligence in psychiatry
Researchers are studying how artificial intelligence (AI) can be used to better detect, prognosticate and subgroup diseases. The idea that AI might advance medicine’s understanding of biological categories of psychiatric disorders, as well as provide better treatments, is appealing given the historical challenges with prediction, diagnosis and treatment in psychiatry. Given the power of AI to analyse vast amounts of information, some clinicians m…
Digital tools for youth health promotion
Although digital health promotion (DHP) technologies for young people are increasingly available in low- and middle-income countries (LMICs), there has been insufficient research investigating whether existing ethical and policy frameworks are adequate to address the challenges and promote the technological opportunities in these settings. In an effort to fill this gap and as part of a larger research project, in November 2022, we conducted a wor…
“There's more to recovery than just weight gain”
Machine learning used to study risk factors for chronic diseases
OBJECTIVES: Machine learning (ML) has received significant attention for its potential to process and learn from vast amounts of data. Our aim was to perform a scoping review to identify studies that used ML to study risk factors for chronic diseases at a population level, notably those that incorporated methods to mitigate algorithmic bias. We focused on ML applications for the most common risk factors for chronic disease: tobacco use, alcohol u…
Medicine (5 obras) · Artificial Intelligence (3 obras) · Computer Science (3 obras) · Political science (3 obras) · Psychology (3 obras) · Artificial Intelligence in Healthcare and Education (2 obras) · Criminology (2 obras) · Digital Mental Health Interventions (2 obras) · Poison control (2 obras) · Sociology (2 obras)