AIMC Topic: Retrospective Studies

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A neural network approach to glomerular filtration rate estimation: a single-centre retrospective audit.

Nuclear medicine communications
OBJECTIVES: The 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation without race correction factor is frequently used for an estimate of glomerular filtration rate (eGFR) and to support a single-sample GFR regime. This study exa...

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study.

JMIR formative research
BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinic...

Prediction of Seronegative Hashimoto's thyroiditis using machine learning models based on ultrasound radiomics: a multicenter study.

BMC immunology
BACKGROUND: Seronegative Hashimoto's thyroiditis is often underdiagnosed due to the lack of antibody markers. Combining ultrasound radiomics with machine learning offers potential for early detection in patients with normal thyroid function.

AIAIAI: AI insights on amassing influence in AI-related publications - an AI-assisted retrospective analysis into AI-related publication.

BMJ health & care informatics
OBJECTIVES: This study analyses the trend of artificial intelligence (AI)-related publications in the medical field over the past decade and demonstrates the potential of AI in automating data analysis. We hypothesise exponential growth in AI-related...

Deep learning model for detecting cystoid fluid collections on optical coherence tomography in X-linked retinoschisis patients.

Acta ophthalmologica
PURPOSE: To validate a deep learning (DL) framework for detecting and quantifying cystoid fluid collections (CFC) on spectral-domain optical coherence tomography (SD-OCT) in X-linked retinoschisis (XLRS) patients.

Deep learning prediction of mammographic breast density using screening data.

Scientific reports
This study investigated a series of deep learning (DL) models for the objective assessment of four categories of mammographic breast density (e.g., fatty, scattered, heterogeneously dense, and extremely dense). A retrospective analysis was conducted ...

Leveraging Artificial Intelligence to Uncover Symptom Burden in Palliative Care: Analysis of Nonscheduled Visits Using a Phi-3 Small Language Model.

JCO global oncology
PURPOSE: This study aimed to differentiate nonscheduled visits (NSVs) in an outpatient palliative care setting that are driven by or accompanied by uncontrolled symptoms from those that are administrative or routine, such as prescription refills and ...

A machine learning model to predict intradialytic hypotension in pediatric continuous kidney replacement therapy.

Pediatric nephrology (Berlin, Germany)
BACKGROUND: Intradialytic hypotension (IDH) is associated with mortality in adults undergoing intermittent hemodialysis, but this relationship is unclear in critically ill children receiving continuous kidney replacement therapy (CKRT). We aim to eva...