AIMC Topic: Adenoma

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Prediction of recurrence after surgery for pituitary adenoma using machine learning- based models: systematic review and meta-analysis.

BMC endocrine disorders Jul 1, 2025
BACKGROUND: Predicting pituitary adenoma (PA) recurrence after surgical resection is critical for guiding clinical decision-making, and machine learning (ML) based models show great promise in improving the accuracy of these predictions. These models...
Machine Learning Prognosis Humans Pituitary Neoplasms Adenoma Neoplasm Recurrence, Local
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Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model.

BMC medical imaging May 3, 2025
OBJECTIVE: Pituitary adenomas (PAs), craniopharyngiomas (CRs), Rathke's cleft cysts (RCCs), and tuberculum sellar meningiomas (TSMs) are common sellar region lesions with similar imaging characteristics, making differential diagnosis challenging. Thi...
Pituitary Neoplasms Adenoma Diagnosis, Differential Meningioma Middle Aged Adolescent Support Vector Machine Magnetic Resonance Imaging Meningeal Neoplasms Sella Turcica Craniopharyngioma Central Nervous System Cysts Machine Learning Retrospective Studies Female Humans Aged Young Adult Adult Radiomics Male
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Microbiome and fragmentation pattern of blood cell-free DNA and fecal metagenome enhance colorectal cancer micro-dysbiosis and diagnosis analysis: a proof-of-concept study.

mSystems Apr 29, 2025
Colorectal cancer (CRC) is the third most common cancer, and it can be prevented by performing early screening. As a hallmark of cancer, the human microbiome plays important roles in the occurrence and development of CRC. Recently, the blood microbio...
Gastrointestinal Microbiome Dysbiosis Cell-Free Nucleic Acids Adenoma Colorectal Neoplasms Male Middle Aged Feces Humans Female Aged Adult Microbiota Proof of Concept Study Metagenome
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A semantic segmentation model for automatic precise identification of pituitary microadenomas with preoperative MRI.

Neuroradiology Apr 4, 2025
PURPOSE: Magnetic resonance imaging (MRI) is an essential technique for diagnosing pituitary adenomas; however, it is also challenging for neurosurgeons to use it to precisely identify some types of microadenomas. A novel neural network model was dev...
Image Interpretation, Computer-Assisted Humans Semantics Contrast Media Neural Networks, Computer Preoperative Care Magnetic Resonance Imaging Adult Pituitary Neoplasms Male Adenoma Female Middle Aged Aged
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Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

Journal of digestive diseases Apr 2, 2025
OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high-risk adenomas among colorectal polyps ≤ 10 mm with standard white-light endoscopy.
Colonic Polyps Deep Learning Humans ROC Curve Colorectal Neoplasms Adenoma Colonoscopy Diagnosis, Differential Diagnosis, Computer-Assisted
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A Novel Natural Language Processing Tool Improves Colonoscopy Auditing of Adenoma and Serrated Polyp Detection Rates.

Journal of gastroenterology and hepatology Mar 31, 2025
BACKGROUND AND STUDY AIMS: Determining adenoma detection rate (ADR) and serrated polyp detection rate (SDR) can be challenging as they usually involve manual matching of colonoscopy and histology reports. This study aimed to validate a Natural Langua...
Quality Indicators, Health Care Medical Audit Adenoma Natural Language Processing Humans Colonic Neoplasms Colonic Polyps Female Male Colonoscopy
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Non-invasive classification of non-neoplastic and neoplastic gallbladder polyps based on clinical imaging and ultrasound radiomics features: An interpretable machine learning model.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Feb 25, 2025
BACKGROUND: Gallbladder (GB) adenomas, precancerous lesions for gallbladder carcinoma (GBC), lack reliable non-invasive tools for preoperative differentiation of neoplastic polyps from cholesterol polyps. This study aimed to evaluate an interpretable...
Humans Machine Learning Retrospective Studies Female Gallbladder Diseases Middle Aged Aged Gallbladder Neoplasms Ultrasonography Adult Cholecystectomy Adenoma Radiomics Polyps Diagnosis, Differential Male
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Eye-tracking dataset of endoscopist-AI teaming during colonoscopy: Retrospective and real-time acquisition.

Scientific data Feb 5, 2025
Recent studies have demonstrated that integrating AI into colonoscopy procedures significantly improves the adenoma detection rate (ADR) and reduces the adenoma miss rate (AMR). However, few studies address the critical issue of endoscopist-AI collab...
Humans Artificial Intelligence Retrospective Studies Colonoscopy Eye-Tracking Technology Adenoma
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Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study.

World journal of surgical oncology Jan 28, 2025
BACKGROUND: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenomas with a higher preoperative malignancy risk is crucial. This study aimed to establish a preoperativ...
Support Vector Machine Follow-Up Studies Humans Adenoma Machine Learning Diagnosis, Differential Retrospective Studies Cholesterol Male Prognosis Female Gallbladder Neoplasms Middle Aged Aged Polyps Ultrasonography Adult ROC Curve
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Machine learning algorithms for predicting delayed hyponatremia after transsphenoidal surgery for patients with pituitary adenoma.

Scientific reports Jan 9, 2025
This study aimed to develop and validate machine learning (ML) models to predict the occurrence of delayed hyponatremia after transsphenoidal surgery for pituitary adenoma. We retrospectively collected clinical data on patients with pituitary adenoma...
Adenoma Hyponatremia Middle Aged Postoperative Complications ROC Curve Pituitary Neoplasms Female Aged Adult Male Machine Learning Algorithms Prospective Studies Retrospective Studies Humans
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