Preoperative Care

Artificial intelligence can help individualize Wilms tumor treatment by predicting tumor response to preoperative chemotherapy.

Investigative and clinical urology Jan 1, 2025

PURPOSE: To create a computer-aided prediction (CAP) system to predict Wilms tumor (WT) responsiveness to preoperative chemotherapy (PC) using pre-therapy contrast-enhanced computed tomography (CECT).

Retrospective Studies Tomography, X-Ray Computed Female Male Infant Humans Artificial Intelligence Precision Medicine Kidney Neoplasms Nephrectomy Preoperative Care Vincristine Wilms Tumor Dactinomycin Adolescent Child, Preschool Child Antineoplastic Combined Chemotherapy Protocols Treatment Outcome

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Automatic Landmark Detection for Preoperative Planning of High Tibial Osteotomy Using Traditional Feature Extraction and Deep Learning Methods.

The international journal of medical robotics + computer assisted surgery : MRCAS Dec 1, 2024

BACKGROUND: Automatic High Tibial Osteotomy (HTO) landmark detection methods promise to improve the effectiveness and standardisation of HTO preoperative planning. Unfortunately, due to the limited number of HTO datasets, existing methods are less ro...

Humans Algorithms Female Adult Male Tibia Deep Learning Preoperative Care Image Processing, Computer-Assisted Anatomic Landmarks Surgery, Computer-Assisted Osteotomy

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Novel deep learning radiomics model for preoperative evaluation of hepatocellular carcinoma differentiation based on computed tomography data.

Clinical and translational medicine Nov 1, 2021

Humans Deep Learning Tomography, X-Ray Computed Liver Neoplasms Female Carcinoma, Hepatocellular Aged Cell Differentiation Male Preoperative Care Middle Aged

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Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

European journal of radiology Oct 1, 2020

PURPOSE: To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade.

Retrospective Studies Female Reproducibility of Results Male Middle Aged Humans Machine Learning Preoperative Care Meningioma Meningeal Neoplasms Multiparametric Magnetic Resonance Imaging ROC Curve Predictive Value of Tests Area Under Curve Neoplasm Grading Image Interpretation, Computer-Assisted

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A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas.

Scientific reports Jul 16, 2020

Glioblastoma is the most common malignant brain parenchymal tumor yet remains challenging to treat. The current standard of care-resection and chemoradiation-is limited in part due to the genetic heterogeneity of glioblastoma. Previous studies have i...

Chromosomes, Human, Pair 10 Chromosomes, Human, Pair 7 X-linked Nuclear Protein Magnetic Resonance Imaging Cyclin-Dependent Kinase Inhibitor p16 Decision Trees Glioblastoma Gene Expression Mutation Aneuploidy Image Interpretation, Computer-Assisted Female Isocitrate Dehydrogenase Sensitivity and Specificity Preoperative Care Biomarkers, Tumor Humans Brain Neoplasms Artificial Intelligence Male Retrospective Studies

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Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society Jul 1, 2020

OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...

Aged, 80 and over Sensitivity and Specificity Male Middle Aged Deep Learning Artificial Intelligence Retrospective Studies Female Esophageal Squamous Cell Carcinoma Reproducibility of Results Preoperative Care Aged Endoscopic Mucosal Resection Humans Neoplasm Invasiveness Neural Networks, Computer Area Under Curve Esophageal Neoplasms Japan Outcome Assessment, Health Care

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Single-Port Robotic Urological Surgery Using Purpose-Built Single-Port Surgical System: Single-Institutional Experience With the First 100 Cases.

Urology Jun 1, 2020

OBJECTIVES: To present a comprehensive report regarding our experience with single-port robotic surgery in our first 100 consecutive patients. We describe the diversity of procedures that can be performed with this platform as well as the challenges ...

Urologic Surgical Procedures Outcome and Process Assessment, Health Care Male Humans Middle Aged Female Aged Minimally Invasive Surgical Procedures Robotic Surgical Procedures Preoperative Care Conversion to Open Surgery Intraoperative Complications Postoperative Complications Urologic Neoplasms Robotics

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A machine learning model to precisely immunohistochemically classify pituitary adenoma subtypes with radiomics based on preoperative magnetic resonance imaging.

European journal of radiology Apr 1, 2020

PURPOSE: The type of pituitary adenoma (PA) cannot be clearly recognized with preoperative magnetic resonance imaging (MRI) but can be classified with immunohistochemical staining after surgery. In this study, a model to precisely immunohistochemical...

Machine Learning Retrospective Studies Female Aged Young Adult Adult Male Middle Aged Adolescent Magnetic Resonance Imaging Preoperative Care Humans Pituitary Neoplasms Pituitary Gland Adenoma Bayes Theorem Image Interpretation, Computer-Assisted Immunohistochemistry

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Automatic detection of perforators for microsurgical reconstruction.

Breast (Edinburgh, Scotland) Apr 1, 2020

The deep inferior epigastric perforator (DIEP) is the most commonly used free flap in mastectomy reconstruction. Preoperative imaging techniques are routinely used to detect location, diameter and course of perforators, with direct intervention from ...

Preoperative Care Free Tissue Flaps Perforator Flap Epigastric Arteries Software Humans Female Artificial Intelligence Pilot Projects Image Processing, Computer-Assisted Mammaplasty

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Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines.

Annals of surgical oncology Mar 1, 2020

BACKGROUND: There is an ongoing debate about expanding the resection criteria for hepatocellular carcinoma (HCC) beyond the Barcelona Clinic Liver Cancer (BCLC) guidelines. We sought to determine the factors that held the most prognostic weight in th...

Liver Neoplasms Carcinoma, Hepatocellular Follow-Up Studies Practice Guidelines as Topic Neoplasm Staging Humans Survival Rate Hepatectomy Tumor Burden Machine Learning Biomarkers, Tumor Preoperative Care Retrospective Studies Male Female Middle Aged Aged Postoperative Complications

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AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Artificial intelligence can help individualize Wilms tumor treatment by predicting tumor response to preoperative chemotherapy.

Automatic Landmark Detection for Preoperative Planning of High Tibial Osteotomy Using Traditional Feature Extraction and Deep Learning Methods.

Novel deep learning radiomics model for preoperative evaluation of hepatocellular carcinoma differentiation based on computed tomography data.

Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas.

Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Single-Port Robotic Urological Surgery Using Purpose-Built Single-Port Surgical System: Single-Institutional Experience With the First 100 Cases.

A machine learning model to precisely immunohistochemically classify pituitary adenoma subtypes with radiomics based on preoperative magnetic resonance imaging.

Automatic detection of perforators for microsurgical reconstruction.

Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines.

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