AIMC Topic: Electronic Health Records

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An effective multi-step feature selection framework for clinical outcome prediction using electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Identifying key variables is essential for developing clinical outcome prediction models based on high-dimensional electronic medical records (EMR). However, despite the abundance of feature selection (FS) methods available, challenges re...

Adaptable graph neural networks design to support generalizability for clinical event prediction.

Journal of biomedical informatics
OBJECTIVE: While many machine learning and deep learning-based models for clinical event prediction leverage various data elements from electronic healthcare records such as patient demographics and billing codes, such models face severe challenges w...

Exploring Potential Medications for Alzheimer's Disease with Psychosis by Integrating Drug Target Information into Deep Learning Models: A Data-Driven Approach.

International journal of molecular sciences
Approximately 50% of Alzheimer's disease (AD) patients develop psychotic symptoms, leading to a subtype known as psychosis in AD (AD + P), which is associated with accelerated cognitive decline compared to AD without psychosis. Currently, no FDA-appr...

Prediction of 90 day mortality in elderly patients with acute HF from e-health records using artificial intelligence.

ESC heart failure
AIMS: Mortality risk after hospitalization for heart failure (HF) is high, especially in the first 90 days. This study aimed to construct a model automatically predicting 90 day post-discharge mortality using electronic health record (EHR) data 48 h ...

Reliability-enhanced data cleaning in biomedical machine learning using inductive conformal prediction.

PLoS computational biology
Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. Existing approac...

Empowering large language models for automated clinical assessment with generation-augmented retrieval and hierarchical chain-of-thought.

Artificial intelligence in medicine
BACKGROUND: Understanding and extracting valuable information from electronic health records (EHRs) is important for improving healthcare delivery and health outcomes. Large language models (LLMs) have demonstrated significant proficiency in natural ...

Natural language processing techniques applied to the electronic health record in clinical research and practice - an introduction to methodologies.

Computers in biology and medicine
Natural Language Processing (NLP) has the potential to revolutionise clinical research utilising Electronic Health Records (EHR) through the automated analysis of unstructured free text. Despite this potential, relatively few applications have entere...

Prediction of adverse pregnancy outcomes using machine learning techniques: evidence from analysis of electronic medical records data in Rwanda.

BMC medical informatics and decision making
BACKGROUND: Despite substantial progress in maternal and neonatal health, Rwanda's mortality rates remain high, necessitating innovative approaches to meet health related Sustainable Development Goals (SDGs). By leveraging data collected from Electro...

Using Natural Language Processing Methods to Predict Topics Included in 2019 Ohio Syphilis Disease Intervention Specialist Records.

Sexually transmitted diseases
BACKGROUND: Free-text notes in disease intervention specialist (DIS) records may contain relevant information for sexual transmitted infection control. In their current form, the notes are not analyzable without manual reading, which is labor-intensi...

The good, the bad, and the ugly: Ethical considerations regarding artificial intelligence assistance in administrative physician tasks.

Clinics in dermatology
Artificial intelligence is a powerful tool that can potentially transform the diagnostic, therapeutic, and administrative practice of dermatology. Physicians are expected to complete electronic health record documentation in a timely fashion, prepare...