Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

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A multicenter clinical AI system study for detection and diagnosis of focal liver lesions.

Early and accurate diagnosis of focal liver lesions is crucial for effective treatment and prognosis...

Deep learning algorithm-based multimodal MRI radiomics and pathomics data improve prediction of bone metastases in primary prostate cancer.

PURPOSE: Bone metastasis is a significant contributor to morbidity and mortality in advanced prostat...

Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.

OBJECTIVE: This study aimed to establish a combined method of radiomics and deep learning (DL) in ma...

Role of the artificial intelligence in the management of T1 colorectal cancer.

Approximately 10% of submucosal invasive (T1) colorectal cancers demonstrate extraintestinal lymph n...

Cancer detection and classification using a simplified binary state vector machine.

Cancer is an invasive and malignant growth of cells and is known to be one of the most fatal disease...

Prediction of microvascular invasion and pathological differentiation of hepatocellular carcinoma based on a deep learning model.

PURPOSE: To develop a deep learning (DL) model based on preoperative contrast-enhanced computed tomo...

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor...

[Feeling analysis on allergen immunotherapy on using an unsupervised machine learning model].

OBJECTIVE: Analyze feelings about allergen-specific immunotherapy on using the VADER model VADER ()...

Advances in next-generation sequencing and emerging technologies for hematologic malignancies.

Innovations in molecular diagnostics have often evolved through the study of hematologic malignancie...

Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy.

OBJECTIVE: Fast progression (FP) represents a desperate situation for advanced non-small cell lung c...

Assessment of brain tumor detection techniques and recommendation of neural network.

OBJECTIVES: Brain tumor classification is amongst the most complex and challenging jobs in the compu...

Deep-learning model to improve histological grading and predict upstaging of atypical ductal hyperplasia / ductal carcinoma in situ on breast biopsy.

AIMS: Risk stratification of atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS), ...

Artificial intelligence assisted patient blood and urine droplet pattern analysis for non-invasive and accurate diagnosis of bladder cancer.

Bladder cancer is one of the most common cancer types in the urinary system. Yet, current bladder ca...

Choline Carboxylic Acid Ionic Liquid-stabilized Anisotropic Gold Nanoparticles for Photothermal Therapy.

Gold nanoparticles (AuNPs) are commonly used in cancer research due to their unique physical and opt...

Oral squamous cell carcinoma detection using EfficientNet on histopathological images.

INTRODUCTION: Oral Squamous Cell Carcinoma (OSCC) poses a significant challenge in oncology due to t...

Deep learning diagnostic performance and visual insights in differentiating benign and malignant thyroid nodules on ultrasound images.

This study aims to construct and evaluate a deep learning model, utilizing ultrasound images, to acc...

A comparative analysis of CNN-based deep learning architectures for early diagnosis of bone cancer using CT images.

Bone cancer is a rare in which cells in the bone grow out of control, resulting in destroying the no...

Early port site and peritoneal metastasis following robot-assisted radical cystectomy: a rare case report.

Radical cystectomy with pelvic lymph node dissection is the recommended treatment for managing muscl...

Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology.

In histopathology practice, scanners, tissue processing, staining, and image acquisition protocols v...

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