AIMC Topic: Retrospective Studies

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Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients.

PloS one
The goal of this study was to employ novel deep-learning convolutional-neural-network (CNN) to predict pathological complete response (PCR), residual cancer burden (RCB), and progression-free survival (PFS) in breast cancer patients treated with neoa...

Comparison of Robot-Assisted Percutaneous Cannulated Screws Versus Open Reduction and Internal Fixation in Calcaneal Fractures.

Orthopaedic surgery
OBJECTIVE: Accurate placement of the screws is challenging in percutaneous cannulated screw fixation of calcaneal fractures, and robot-assisted (RA) surgery enhances the accuracy. We investigated the outcome of percutaneous cannulated screw fixation ...

Differential diagnosis of prostate cancer and benign prostatic hyperplasia based on DCE-MRI using bi-directional CLSTM deep learning and radiomics.

Medical & biological engineering & computing
Dynamic contrast-enhanced MRI (DCE-MRI) is routinely included in the prostate MRI protocol for a long time; its role has been questioned. It provides rich spatial and temporal information. However, the contained information cannot be fully extracted ...

Prediction of postoperative infection in elderly using deep learning-based analysis: an observational cohort study.

Aging clinical and experimental research
Elderly patients are susceptible to postoperative infections with increased mortality. Analyzing with a deep learning model, the perioperative factors that could predict and/or contribute to postoperative infections may improve the outcome in elderly...

Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification.

The British journal of radiology
OBJECTIVES: To precisely predict prostate cancer (PCa) risk stratification, we constructed a machine learning (ML) model based on magnetic resonance imaging (MRI) radiomic features.

Robotic guidance for percutaneous placement of triangular osteosynthesis in vertically unstable sacrum fractures: a single-center retrospective study.

Journal of orthopaedic surgery and research
BACKGROUND: To evaluate the effectiveness and safety of robot-aided percutaneous triangular osteosynthesis combined with close reduction for vertically unstable sacrum fractures (VUSFs).

Comparison of short-term outcomes of robotic and laparoscopic transabdominal peritoneal repair for unilateral inguinal hernia: a propensity-score matched analysis.

Hernia : the journal of hernias and abdominal wall surgery
PURPOSE: This study aimed to compare perioperative outcomes of robotic and laparoscopic transabdominal peritoneal repair (TAPP) for unilateral inguinal hernia.

Identification of Asymptomatic COVID-19 Patients on Chest CT Images Using Transformer-Based or Convolutional Neural Network-Based Deep Learning Models.

Journal of digital imaging
Novel coronavirus disease 2019 (COVID-19) has rapidly spread throughout the world; however, it is difficult for clinicians to make early diagnoses. This study is to evaluate the feasibility of using deep learning (DL) models to identify asymptomatic ...

Computer-aided diagnosis in prostate cancer: a retrospective evaluation of the Watson Elementary system for preoperative tumor characterization in patients treated with robot-assisted radical prostatectomy.

World journal of urology
PURPOSE: Computer-aided diagnosis (CAD) may improve prostate cancer (PCa) detection and support multiparametric magnetic resonance imaging (mpMRI) readers for better characterization. We evaluated Watson Elementary (WE) CAD system results referring t...

Development and Validation of a Deep Learning Algorithm to Differentiate Colon Carcinoma From Acute Diverticulitis in Computed Tomography Images.

JAMA network open
IMPORTANCE: Differentiating between malignant and benign etiology in large-bowel wall thickening on computed tomography (CT) images can be a challenging task. Artificial intelligence (AI) support systems can improve the diagnostic accuracy of radiolo...