Oncology/Hematology

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method.

White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the immune system. They are also known as "defender cells." But the imbalance in the number of WBCs in the blood can be hazardous. Leukemia is the most common blood cancer caused by an overabundance of WBCs in the immune system. Acute lymphocytic leukemia (ALL) usually occurs when the bone marrow creates many ...

Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma.

PURPOSE: How to discriminate different risks of recurrent nasopharyngeal carcinoma (rNPC) patients and guide individual treatment has become of great importance. This study aimed to explore the associations between deep learning signatures and biological functions as well as survival in (rNPC) patients.

A novel liver cancer diagnosis method based on patient similarity network and DenseGCN.

Liver cancer is the main malignancy in terms of mortality rate, accurate diagnosis can help the treatment outcome of liver cancer. Patient similarity ...

Predictive models for clinical decision making: Deep dives in practical machine learning.

The deployment of machine learning for tasks relevant to complementing standard of care and advancing tools for precision health has gained much atten...

Gradient tree boosting and network propagation for the identification of pan-cancer survival networks.

Cancer survival prediction is typically done with uninterpretable machine learning techniques, e.g., gradient tree boosting. Therefore, additional ste...

Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology.

Molecular tests are necessary to stratify cancer patients for targeted therapy. However, high cost and technical barriers limit the application of the...

Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning.

Oral squamous cell carcinoma (OSCC) is prevalent around the world and is associated with poor prognosis. OSCC is typically diagnosed from tissue biops...

Artificial intelligence to identify genetic alterations in conventional histopathology.

Precision oncology relies on the identification of targetable molecular alterations in tumor tissues. In many tumor types, a limited set of molecular ...

Use of deep learning to predict the need for aggressive nutritional supplementation during head and neck radiotherapy.

PURPOSE/OBJECTIVES: Radiation therapy (RT) for the treatment of patients with head and neck cancer (HNC) leads to side effects that can limit a person...

Finding a Suitable Class Distribution for Building Histological Images Datasets Used in Deep Model Training-The Case of Cancer Detection.

The class distribution of a training dataset is an important factor which influences the performance of a deep learning-based system. Understanding th...

Robot-assisted thoracic surgery for intercostal cavernous hemangioma.

Intercostal cavernous hemangioma is extremely rare among benign vascular tumors. Achieving a definitive diagnosis preoperatively by radiographic exami...

Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.

Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaningful cancer drivers is an important and challenging...

The future of early cancer detection.

A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival...

Robot-Assisted Radical Prostatectomy for Potential Cancer Control in Patients with Metastatic Prostate Cancer.

Recently, cytoreductive prostatectomy for metastatic prostate cancer (mPCa) has been associated with improved oncological outcomes. This study was aim...

Improved Artificial Neural Network with State Order Dataset Estimation for Brain Cancer Cell Diagnosis.

Brain cancer is one of the cell synthesis diseases. Brain cancer cells are analyzed for patient diagnosis. Due to this composite cell, the conceptual ...

Robotic CME in obese patients: advantage of robotic ultrasound scan for vascular dissection.

Complete mesocolic excision (CME) in right-sided colon cancers appears to confer oncological benefits compared to conventional colectomy. Identificati...

A deep learning model to classify and detect brain abnormalities in portable microwave based imaging system.

Automated classification and detection of brain abnormalities like a tumor(s) in reconstructed microwave (RMW) brain images are essential for medical ...

Deep learning model for tongue cancer diagnosis using endoscopic images.

In this study, we developed a deep learning model to identify patients with tongue cancer based on a validated dataset comprising oral endoscopic imag...

Label-Free Differentiation of Cancer and Non-Cancer Cells Based on Machine-Learning-Algorithm-Assisted Fast Raman Imaging.

This paper proposes a rapid, label-free, and non-invasive approach for identifying murine cancer cells (B16F10 melanoma cancer cells) from non-cancer ...

MBP-11901 Inhibits Tumor Growth of Hepatocellular Carcinoma through Multitargeted Inhibition of Receptor Tyrosine Kinases.

Hepatocellular carcinomas (HCCs) are aggressive tumors with a poor prognosis. Approved first-line treatments include sorafenib, lenvatinib, and a comb...