AIMC Topic: Retrospective Studies

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A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study.

European journal of pediatrics
UNLABELLED: Congenital diaphragmatic hernia (CDH) has high morbidity and mortality rates. This study aimed to develop a machine learning (ML) algorithm to predict outcomes based on prenatal and early postnatal data. This retrospective observational c...

AI classification of knee prostheses from plain radiographs and real-world applications.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery ...

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance.

The international journal of cardiovascular imaging
Invasive coronary physiology is underused and carries risks/costs. Artificial Intelligence (AI) might enable non-invasive physiology from invasive coronary angiography (CAG), possibly outperforming humans, but has seldom been explored, especially for...

A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: To construct and assess a deep learning (DL) signature that employs computed tomography imaging to predict the expression status of programmed cell death ligand 1 in patients with bladder cancer (BCa).

Artificial Intelligence for Teaching Case Curation: Evaluating Model Performance on Imaging Report Discrepancies.

Academic radiology
RATIONALE AND OBJECTIVES: Assess the feasibility of using a large language model (LLM) to identify valuable radiology teaching cases through report discrepancy detection.

Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.

Nutrients
: Diet plays an important role in preventing and managing the progression from prediabetes to type 2 diabetes mellitus (T2DM). This study aims to develop prediction models incorporating specific dietary indicators and explore the performance in T2DM ...

Prediction of tumor spread through air spaces with an automatic segmentation deep learning model in peripheral stage I lung adenocarcinoma.

Respiratory research
BACKGROUND: To evaluate the clinical applicability of deep learning (DL) models based on automatic segmentation in preoperatively predicting tumor spread through air spaces (STAS) in peripheral stage I lung adenocarcinoma (LUAD).

Hand X-rays findings and a disease screening for Turner syndrome through deep learning model.

BMC pediatrics
BACKGROUND: Turner syndrome (TS) is one of the important causes of short stature in girls, but there are cases of misdiagnosis and missed diagnosis in clinical practice. Our aim is to analyze the hand skeletal characteristics of TS patients and estab...