AIMC Topic: Continuity of Patient Care

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Causal machine learning models for predicting low birth weight in midwife-led continuity care intervention in North Shoa Zone, Ethiopia.

BMC medical informatics and decision making
BACKGROUND: Low birth weight (LBW) is a critical global health issue that affects infants disproportionately, particularly in developing countries. This study adopted causal machine learning (CML) algorithms for predicting LBW in newborns, drawing fr...

An ethical assessment of professional opinions on concerns, chances, and limitations of the implementation of an artificial intelligence-based technology into the geriatric patient treatment and continuity of care.

GeroScience
With the introduction of an artificial intelligence-based dashboard into the clinic, the project SURGE-Ahead responds to the importance of improving perioperative geriatric patient treatment and continuity of care. The use of artificial intelligence ...

Effectiveness of continuity of care after robot-assisted laparoscopic adrenalectomy under ambulatory mode: a single-center intervention study.

Journal of robotic surgery
To investigate the effectiveness of continuity of care after robot-assisted adrenal tumor resection under ambulatory mode. Patients who underwent robot-assisted laparoscopic adrenalectomy (RALA) in the ambulatory surgery department and urology depart...

Predicting Continuity of Asthma Care Using a Machine Learning Model: Retrospective Cohort Study.

International journal of environmental research and public health
Continuity of care (COC) has been shown to possess numerous health benefits for chronic diseases. Specifically, the establishment of its level can facilitate clinical decision-making and enhanced allocation of healthcare resources. However, the use o...

Predicting preventable hospital readmissions with causal machine learning.

Health services research
OBJECTIVE: To assess both the feasibility and potential impact of predicting preventable hospital readmissions using causal machine learning applied to data from the implementation of a readmissions prevention intervention (the Transitions Program).

Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits.

Breast (Edinburgh, Scotland)
Integrated breast cancer care is complex, marked by multiple hand-offs between primary care and specialists over an extensive period of time. Communication is essential for treatment compliance, lowering error and complication risk, as well as handli...

Use of Machine Learning to Identify Follow-Up Recommendations in Radiology Reports.

Journal of the American College of Radiology : JACR
PURPOSE: The aims of this study were to assess follow-up recommendations in radiology reports, develop and assess traditional machine learning (TML) and deep learning (DL) models in identifying follow-up, and benchmark them against a natural language...

Evaluation of an automated knowledge-based textual summarization system for longitudinal clinical data, in the intensive care domain.

Artificial intelligence in medicine
OBJECTIVES: To examine the feasibility of the automated creation of meaningful free-text summaries of longitudinal clinical records, using a new general methodology that we had recently developed; and to assess the potential benefits to the clinical ...

Characteristics of outpatient clinical summaries in the United States.

International journal of medical informatics
In the United States, federal regulations require that outpatient practices provide a clinical summary to ensure that patients understand what transpired during their appointment and what to do before the next visit. To determine whether clinical sum...

Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury.

Health economics
For a continuous treatment, the generalised propensity score (GPS) is defined as the conditional density of the treatment, given covariates. GPS adjustment may be implemented by including it as a covariate in an outcome regression. Here, the unbiased...