AIMC Topic: Time Factors

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Investigating Symptom Duration Using Current Status Data: A Case Study of Postacute COVID-19 Syndrome.

Epidemiology (Cambridge, Mass.)
BACKGROUND: For infectious diseases, characterizing symptom duration is of clinical and public health importance. Symptom duration may be assessed by surveying infected individuals and querying symptom status at the time of survey response. For examp...

A systematic comparison of short-term and long-term mortality prediction in acute myocardial infarction using machine learning models.

BMC medical informatics and decision making
BACKGROUND AND OBJECTIVE: The machine learning (ML) models for acute myocardial infarction (AMI) are considered to have better predictive ability for mortality compared to conventional risk scoring models. However, previous ML prediction models have ...

Predicting mortality risk following major lower extremity amputation using machine learning.

Journal of vascular surgery
OBJECTIVE: Major lower extremity amputation for advanced vascular disease involves significant perioperative risks. Although outcome prediction tools could aid in clinical decision-making, they remain limited. To address this, we developed machine le...

Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study.

BMC medical informatics and decision making
BACKGROUND: Timely prehospital care is crucial for patients presenting with high-risk time-sensitive (HRTS) conditions. However, the interplay between response time and demographic factors in patients with breathing problems remains insufficiently un...

Unlocking the Potential of Wear Time of a Wearable Device to Enhance Postpartum Depression Screening and Detection: Cross-Sectional Study.

JMIR formative research
BACKGROUND: Postpartum depression (PPD) is a mood disorder affecting 1 in 7 women after childbirth that is often underscreened and underdetected. If not diagnosed and treated, PPD is associated with long-term developmental challenges in the child and...

Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population.

Cardiovascular diabetology
BACKGROUND AND OBJECTIVE: Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabetes risk remains unclear. This study aimed to comprehensively evaluate the associations between six ...

Associations between the 24-h Activity Daily Cycle and Incident Dementia.

Medicine and science in sports and exercise
BACKGROUND: Physical activity, sedentary behavior (SB), and sleep all impact the risk of incident dementia, however, engagement in these activities is constrained by the 24-h day. Increasing time spent in one activity necessarily reduces time spent i...

Characterization of Effective Half-Life for Instant Single-Time-Point Dosimetry Using Machine Learning.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Single-time-point (STP) image-based dosimetry offers a more convenient approach for clinical practice in radiopharmaceutical therapy (RPT) compared with conventional multiple-time-point image-based dosimetry. Despite numerous advancements, current ST...