AIMC Topic: Retrospective Studies

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The pathological risk score: A new deep learning-based signature for predicting survival in cervical cancer.

Cancer medicine
PURPOSE: To develop and validate a deep learning-based pathological risk score (RS) with an aim of predicting patients' prognosis to investigate the potential association between the information within the whole slide image (WSI) and cervical cancer ...

Comparison of machine learning classification techniques to predict implantation success in an IVF treatment cycle.

Reproductive biomedicine online
RESEARCH QUESTION: Which machine learning model predicts the implantation outcome better in an IVF cycle? What is the importance of each variable in predicting the implantation outcome in an IVF cycle?

Robot-assisted versus conventional laparoscopic partial nephrectomy for renal hilar tumors: Parenchymal preservation and functional recovery.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVE: To determine whether robot-assisted laparoscopic partial nephrectomy (RALPN) can benefit patients in terms of functional recovery in the treatment of renal hilar tumors compared to conventional laparoscopic partial nephrectomy (CLPN).

Deep Learning-based Post Hoc CT Denoising for Myocardial Delayed Enhancement.

Radiology
Background To improve myocardial delayed enhancement (MDE) CT, a deep learning (DL)-based post hoc denoising method supervised with averaged MDE CT data was developed. Purpose To assess the image quality of denoised MDE CT images and evaluate their d...

Use of deep learning to predict postoperative recurrence of lung adenocarcinoma from preoperative CT.

International journal of computer assisted radiology and surgery
PURPOSE: Although surgery is the primary treatment for lung cancer, some patients experience recurrence at a certain rate. If postoperative recurrence can be predicted early before treatment is initiated, it may be possible to provide individualized ...

Prediction Model between Serum Vitamin D and Neurological Deficit in Cerebral Infarction Patients Based on Machine Learning.

Computational and mathematical methods in medicine
OBJECTIVE: Vitamin D is associated with neurological deficits in patients with cerebral infarction. This study uses machine learning to evaluate the prediction model's efficacy of the correlation between vitamin D and neurological deficit in patients...

Evaluation of Traumatic Subdural Hematoma Volume by Using Image Segmentation Assessment Based on Deep Learning.

Computational and mathematical methods in medicine
Rapid and accurate evaluations of hematoma volume can guide the treatment of traumatic subdural hematoma. We aim to explore the consistency between the measurement results of traumatic subdural hematoma (TSDH) using a deep learn-based image segmentat...

Predictors of operative difficulty in robotic low anterior resection for rectal cancer.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
AIM: This study evaluates the relationship of tumour and anatomical features with operative difficulty in robotic low anterior resection performed by four experienced surgeons in a high-volume colorectal cancer practice.

A Newly Designed "SkyWalker" Robot Applied in Total Knee Arthroplasty: A Retrospective Cohort Study for Femoral Rotational Alignment Restoration.

Orthopaedic surgery
OBJECTIVE: This study explored whether robotic arm-assisted total knee arthroplasty (RATKA) has the advantage of restoring femoral rotational alignment compared to conventional total knee arthroplasty (COTKA).