AIMC Topic: Retrospective Studies

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[Development of auxiliary early predicting model for human brucellosis using machine learning algorithm].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]
Using machine learning algorithms to construct an early prediction model of brucellosis to improve the diagnosis efficiency of Brucellosis. This study was a case-control study. 2 381 brucellosis patients from Beijing Ditan Hospital affiliated to Capi...

AI Helps Untangle Cancer Mysteries.

Cancer discovery
Patients with cancer of unknown primary (CUP) face obstacles in accessing treatment because many treatments are indicated only for a specific cancer type. Using retrospective data, researchers proved that OncoNPC, a machine-learning tool, can accurat...

Discard or not discard, that is the question: an international survey across 117 embryologists on the clinical management of borderline quality blastocysts.

Human reproduction (Oxford, England)
STUDY QUESTION: Do embryologists from different European countries agree on embryo disposition decisions ('use' or 'discard') about Day 7 (>144 h post-insemination) and/or low-quality blastocysts (LQB;

[Cox model analysis of curative effect and prognostic factors of oral robot-assisted RPLN dissection for head and neck malignancies].

Shanghai kou qiang yi xue = Shanghai journal of stomatology
PURPOSE: To investigate the efficacy and prognostic factors of oral robot-assisted retropharyngeal lymph node (RPLN) dissection in the treatment of head and neck malignancies.

Deep Learning for Automated Triaging of Stable Chest Radiographs in a Follow-up Setting.

Radiology
Background Most artificial intelligence algorithms that interpret chest radiographs are restricted to an image from a single time point. However, in clinical practice, multiple radiographs are used for longitudinal follow-up, especially in intensive ...

Deep learning to predict esophageal variceal bleeding based on endoscopic images.

The Journal of international medical research
OBJECTIVE: Esophageal varix (EV) bleeding is a particularly serious complications of cirrhosis. Prediction of EV bleeding requires extensive endoscopy experience; it remains unreliable and inefficient. This retrospective cohort study evaluated the fe...

MRI-based Deep Learning Assessment of Amyloid, Tau, and Neurodegeneration Biomarker Status across the Alzheimer Disease Spectrum.

Radiology
Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniq...

Extended Venous Thromboembolism Prophylaxis after Robotic Staging for Endometrial Cancer.

Southern medical journal
OBJECTIVES: Our objectives were to estimate the incidence of venous thromboembolism (VTE) after robotic staging for endometrial cancer and to compare the incidence of VTE in patients who received a single dose of preoperative prophylaxis of enoxapari...

Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis.

Radiology
Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjective interpretation of US images. Purpose To evaluate the agreement and diagnostic performance of radiologists and a deep learning model in grading hepat...

Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers.

Radiology
Background Clinicians consider both imaging and nonimaging data when diagnosing diseases; however, current machine learning approaches primarily consider data from a single modality. Purpose To develop a neural network architecture capable of integra...