AIMC Topic: Retrospective Studies

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Development of machine learning models to predict lymph node metastases in major salivary gland cancers.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: Indications for elective treatment of the neck in patients with major salivary gland cancers are still debated. Our purpose was to develop a machine learning (ML) model able to generate a predictive algorithm to identify lymph node meta...

Early Screening of Colorectal Precancerous Lesions Based on Combined Measurement of Multiple Serum Tumor Markers Using Artificial Neural Network Analysis.

Biosensors
Many patients with colorectal cancer (CRC) are diagnosed in the advanced stage, resulting in delayed treatment and reduced survival time. It is urgent to develop accurate early screening methods for CRC. The purpose of this study is to develop an art...

Learning curves for robotic-assisted spine surgery: an analysis of the time taken for screw insertion, robot setting, registration, and fluoroscopy.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
PURPOSE: The purpose of this study was to clarify the learning curve for robotic-assisted spine surgery. We analyzed the workflow in robotic-assisted spine surgery and investigated how much experience is required to become proficient in robotic-assis...

A deep learning MRI-based signature may provide risk-stratification strategies for nasopharyngeal carcinoma.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
OBJECTIVE: As the prognosis of nasopharyngeal carcinoma (NPC) is influenced by various factors, making it difficult for clinical physicians to predict the outcome, the objective of this study was to develop a deep learning-based signature for risk st...

Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study.

Intensive care medicine
PURPOSE: Whilst survival in paediatric critical care has improved, clinicians lack tools capable of predicting long-term outcomes. We developed a machine learning model to predict poor school outcomes in children surviving intensive care unit (ICU).

Robot-assisted percutaneous pedicle screw placement accuracy compared with alternative guidance in lateral single-position surgery: a systematic review and meta-analysis.

Journal of neurosurgery. Spine
OBJECTIVE: While single-position surgery (SPS) eliminates the need for patient repositioning, the placement of screws in the unconventional lateral position poses unique challenges related to asymmetry relative to the surgical table. Use of robotic g...

Using a deep learning neural network for the identification of malignant cells in effusion cytology material.

Cytopathology : official journal of the British Society for Clinical Cytology
AIM: To evaluate the application of an artificial neural network in the detection of malignant cells in effusion samples.

A single-center retrospective comparative analysis of urinary continence in robotic prostatectomy with a combination of umbilical ligament preservation and Hood technique.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: Data available on the effect of the recently developed Hood technique and its modified iterations in robot-assisted radical prostatectomy on postoperative urinary continence are insufficient. We evaluated the time to achieve urinary conti...

Deep-learning approach to detect childhood glaucoma based on periocular photograph.

Scientific reports
Childhood glaucoma is one of the major causes of blindness in children, however, its diagnosis is of great challenge. The study aimed to demonstrate and evaluate the performance of a deep-learning (DL) model for detecting childhood glaucoma based on ...