AIMC Topic: Retrospective Studies
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Multi-stain deep learning prediction model of treatment response in lupus nephritis based on renal histopathology.
Kidney international
Dec 27, 2024
The response of the kidney after induction treatment is one of the determinants of prognosis in lupus nephritis, but effective predictive tools are lacking. Here, we sought to apply deep learning approaches on kidney biopsies for treatment response p...
Machine learning-based prediction of duodenal stump leakage following laparoscopic gastrectomy for gastric cancer.
Surgery
Dec 27, 2024
BACKGROUND: Duodenal stump leakage is one of the most critical complications following gastrectomy surgery, with a high mortality rate. The present study aimed to establish a predictive model based on machine learning for forecasting the occurrence o...
Analyzing the Effect of Surgical and Corneal Parameters on the Postoperative Refractive Outcomes of Smile in Myopic Eyes Based on Machine Learning.
American journal of ophthalmology
Dec 27, 2024
PURPOSE: To analyze the influence of individual parameters on the postoperative refractive outcomes of small incision lenticule extraction (SMILE) in myopic eyes using machine learning.
Predicting lack of clinical improvement following varicose vein ablation using machine learning.
Journal of vascular surgery. Venous and lymphatic disorders
Dec 26, 2024
OBJECTIVE: Varicose vein ablation is generally indicated in patients with active/healed venous ulcers. However, patient selection for intervention in individuals without venous ulcers is less clear. Tools that predict lack of clinical improvement (LC...
Deep Learning Model for the Differential Diagnosis of Nasal Polyps and Inverted Papilloma by CT Images: A Multicenter Study.
Academic radiology
Dec 26, 2024
RATIONALE AND OBJECTIVES: Nasal polyps (NP) and inverted papilloma (IP) are benign tumors within the nasal cavity, each necessitating distinct treatment approaches. Herein, we investigate the utility of a deep learning (DL) model for distinguishing b...
Predicting the likelihood of readmission in patients with ischemic stroke: An explainable machine learning approach using common data model data.
International journal of medical informatics
Dec 26, 2024
BACKGROUND: Ischemic stroke affects 15 million people worldwide, causing five million deaths annually. Despite declining mortality rates, stroke incidence and readmission risks remain high, highlighting the need for preventing readmission to improve ...
The Potential of SHAP and Machine Learning for Personalized Explanations of Influencing Factors in Myopic Treatment for Children.
Medicina (Kaunas, Lithuania)
Dec 26, 2024
The rising prevalence of myopia is a significant global health concern. Atropine eye drops are commonly used to slow myopia progression in children, but their long-term use raises concern about intraocular pressure (IOP). This study uses SHapley Add...
Pathomics-based machine learning models for predicting pathological complete response and prognosis in locally advanced rectal cancer patients post-neoadjuvant chemoradiotherapy: insights from two independent institutional studies.
BMC cancer
Dec 26, 2024
BACKGROUND: Accurate prediction of pathological complete response (pCR) and disease-free survival (DFS) in locally advanced rectal cancer (LARC) patients undergoing neoadjuvant chemoradiotherapy (NCRT) is essential for formulating effective treatment...
StUdy of Gestational diabetes And Risk using Electronic Data (SUGARED): a population-based cohort study-study protocol.
BMJ open
Dec 26, 2024
INTRODUCTION: The incidence of gestational diabetes mellitus (GDM) in Australia has tripled in the last 20 years. Consequently, over 40 000 pregnancies are now diagnosed as 'higher risk' each year. This has increased antenatal surveillance and obstet...
Hospitals, Public
Routinely Collected Health Data
Predictive Learning Models
Information Storage and Retrieval
Propensity Score
Delivery, Obstetric
Multilevel Analysis
New South Wales
Retrospective Studies
Pregnancy
Female
Risk Assessment
Incidence
Pregnancy Outcome
Humans
Research Design
Logistic Models
Observational Studies as Topic
Diabetes, Gestational
Glucose Tolerance Test
Diagnosis of intracranial aneurysms by computed tomography angiography using deep learning-based detection and segmentation.
Journal of neurointerventional surgery
Dec 26, 2024
BACKGROUND: Detecting and segmenting intracranial aneurysms (IAs) from angiographic images is a laborious task.
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