AIMC Topic: Colonic Neoplasms
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The Diagnostic Ability of GPT-3.5 and GPT-4.0 in Surgery: Comparative Analysis.
Journal of medical Internet research
Sep 10, 2024
BACKGROUND: ChatGPT (OpenAI) has shown great potential in clinical diagnosis and could become an excellent auxiliary tool in clinical practice. This study investigates and evaluates ChatGPT in diagnostic capabilities by comparing the performance of G...
Exploiting histopathological imaging for early detection of lung and colon cancer via ensemble deep learning model.
Scientific reports
Sep 3, 2024
Cancer seems to have a vast number of deaths due to its heterogeneity, aggressiveness, and significant propensity for metastasis. The predominant categories of cancer that may affect males and females and occur worldwide are colon and lung cancer. A ...
Deep neural networks integrating genomics and histopathological images for predicting stages and survival time-to-event in colon cancer.
PloS one
Sep 3, 2024
MOTIVATION: There exists an unexplained diverse variation within the predefined colon cancer stages using only features from either genomics or histopathological whole slide images as prognostic factors. Unraveling this variation will bring about imp...
Accuracy and consistency of publicly available Large Language Models as clinical decision support tools for the management of colon cancer.
Journal of surgical oncology
Aug 19, 2024
BACKGROUND: Large Language Models (LLM; e.g., ChatGPT) may be used to assist clinicians and form the basis of future clinical decision support (CDS) for colon cancer. The objectives of this study were to (1) evaluate the response accuracy of two LLM-...
Deep learning ensemble approach with explainable AI for lung and colon cancer classification using advanced hyperparameter tuning.
BMC medical informatics and decision making
Aug 7, 2024
Lung and colon cancers are leading contributors to cancer-related fatalities globally, distinguished by unique histopathological traits discernible through medical imaging. Effective classification of these cancers is critical for accurate diagnosis ...
Lesion-Decoupling-Based Segmentation With Large-Scale Colon and Esophageal Datasets for Early Cancer Diagnosis.
IEEE transactions on neural networks and learning systems
Aug 5, 2024
Lesions of early cancers often show flat, small, and isochromatic characteristics in medical endoscopy images, which are difficult to be captured. By analyzing the differences between the internal and external features of the lesion area, we propose ...
Metaheuristic integrated machine learning classification of colon cancer using STFT LASSO and EHO feature extraction from microarray gene expressions.
Scientific reports
Jul 17, 2024
The microarray gene expression data poses a tremendous challenge due to their curse of dimensionality problem. The sheer volume of features far surpasses available samples, leading to overfitting and reduced classification accuracy. Thus the dimensio...
An artificial intelligence-designed predictive calculator of conversion from minimally invasive to open colectomy in colon cancer.
Updates in surgery
Jun 26, 2024
Minimally invasive surgery is safe and effective in colorectal cancer. Conversion to open surgery may be associated with adverse effects on treatment outcomes. This study aimed to assess risk factors of conversion from minimally invasive to open cole...
Evaluating the prognostic value of tumor deposits in non-metastatic lymph node-positive colon adenocarcinoma using Cox regression and machine learning.
International journal of colorectal disease
Jun 26, 2024
BACKGROUND: The 8th AJCC TNM staging for non-metastatic lymph node-positive colon adenocarcinoma patients(NMLP-CA) stages solely by lymph node status, irrespective of the positivity of tumor deposits (TD). This study uses machine learning and Cox reg...
Machine learning evaluation of immune infiltrate through digital tumour score allows prediction of survival outcome in a pooled analysis of three international stage III colon cancer cohorts.
EBioMedicine
Jun 15, 2024
BACKGROUND: T-cell immune infiltrates are robust prognostic variables in localised colon cancer. Evaluation of prognosis using artificial intelligence is an emerging field. We evaluated whether machine learning analysis improved prediction of patient...
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