AIMC Topic: Singapore
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Enhancing Small-for-Gestational-Age Prediction: Multi-Country Validation of Nuchal Thickness, Estimated Fetal Weight, and Machine Learning Models.
Prenatal diagnosis
Jan 16, 2025
OBJECTIVE: The first objective is to develop a nuchal thickness reference chart. The second objective is to compare rule-based algorithms and machine learning models in predicting small-for-gestational-age infants.
Protocol for the impact of machine learning-based clinician decision support algorithims in perioperative care (IMAGINATIVE) in Singapore general hospital : a large prospective randomised controlled trial.
BMJ open
Dec 20, 2024
INTRODUCTION: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early id...
Humans
Machine Learning
Prospective Studies
Young Adult
Adult
Male
Middle Aged
Risk Assessment
Intensive Care Units
Female
Aged
Aged, 80 and over
Singapore
Hospitals, General
Perioperative Care
Postoperative Complications
Decision Support Systems, Clinical
Randomized Controlled Trials as Topic
Elective Surgical Procedures
Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO).
BMJ open
Dec 2, 2024
PURPOSE: Coronary CT angiography (CCTA) is well established for the diagnostic evaluation and prognostication of coronary artery disease (CAD). The growing burden of CAD in Asia and the emergence of novel CT-based risk markers highlight the need for ...
Credit and blame for AI-generated content: Effects of personalization in four countries.
Annals of the New York Academy of Sciences
Nov 25, 2024
Generative artificial intelligence (AI) raises ethical questions concerning moral and legal responsibility-specifically, the attributions of credit and blame for AI-generated content. For example, if a human invests minimal skill or effort to produce...
Using Machine Learning Models to Predict Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.
JCO clinical cancer informatics
Nov 22, 2024
PURPOSE: Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling is useful in predicting pathologic complete response (pCR) to NAC. We test machine learning (ML) models to predict pCR in breast cancer and explore met...
Interpretable Machine Learning-Based Risk Score for Predicting 10-Year Corneal Graft Survival After Penetrating Keratoplasty and Deep Anterior Lamellar Keratoplasty in Asian Eyes.
Cornea
Jul 24, 2024
PURPOSE: To predict 10-year graft survival after deep anterior lamellar keratoplasty (DALK) and penetrating keratoplasty (PK) using a machine learning (ML)-based interpretable risk score.
Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits.
Singapore medical journal
Jul 19, 2024
INTRODUCTION: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations ma...
Doctors' perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore.
Frontiers in public health
Jul 1, 2024
OBJECTIVES: The increased utilization of Artificial intelligence (AI) in healthcare changes practice and introduces ethical implications for AI adoption in medicine. We assess medical doctors' ethical stance in situations that arise in adopting an AI...
Does lifelong learning matter for the subjective wellbeing of the elderly? A machine learning analysis on Singapore data.
PloS one
Jun 5, 2024
Our study explores whether lifelong learning is associated with the subjective wellbeing among the elderly in Singapore. Through a primary survey of 300 individuals aged 65 and above, we develop a novel index to capture three different aspects of sub...
Machine-learning based detection of marine mammal vocalizations in snapping-shrimp dominated ambient noise.
Marine environmental research
May 31, 2024
Passive acoustics is an effective method for monitoring marine mammals, facilitating both detection and population estimation. In warm tropical waters, this technique encounters challenges due to the high persistent level of ambient impulsive noise o...
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