AI Medical Compendium Journal:
Current problems in cancer

Showing 1 to 5 of 5 articles

Exploring patient stratification in head and neck squamous cell carcinoma using machine learning techniques: Preliminary results.

Current problems in cancer
BACKGROUND: Head and Neck Squamous Cell Carcinoma (HNSCC) presents a significant challenge in oncology due to its inherent heterogeneity. Traditional staging systems, such as TNM (Tumor, Node, Metastasis), provide limited information regarding patien...

Artificial intelligence-based pathological application to predict regional lymph node metastasis in Papillary Thyroid Cancer.

Current problems in cancer
In this study, a model for predicting lymph node metastasis in papillary thyroid cancer was trained using pathology images from the TCGA(The Cancer Genome Atlas) public dataset of papillary thyroid cancer, and a front-end inference model was trained ...

Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.

Current problems in cancer
Skin cancer, including the highly lethal malignant melanoma, poses a significant global health challenge with a rising incidence rate. Early detection plays a pivotal role in improving survival rates. This study aims to develop an advanced deep learn...

Imaging of lung cancer.

Current problems in cancer
Lung cancer is the leading cause of cancer-related mortality globally. Imaging is essential in the screening, diagnosis, staging, response assessment, and surveillance of patients with lung cancer. Subtypes of lung cancer can have distinguishing imag...

The diagnostic and prognostic roles of serum irisin in bladder cancer.

Current problems in cancer
BACKGROUND: Egypt is among the countries with the highest incidence of bladder cancer (BC). Adipokines involved in BC development. This study aimed to examine the diagnostic and prognostic roles of irisin in BC through its function as an adipokine.