Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Controversial Trials First: Identifying Disagreement Between Clinical Guidelines and New Evidence.

Clinical guidelines integrate latest evidence to support clinical decision-making. As new research f...

Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

Advancing diagnostic testing capabilities such as clinical next generation sequencing methods offer ...

Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review.

BACKGROUND: Improved breast cancer risk assessment models are needed to enable personalized screenin...

Multi-Method Diagnosis of Blood Microscopic Sample for Early Detection of Acute Lymphoblastic Leukemia Based on Deep Learning and Hybrid Techniques.

Leukemia is one of the most dangerous types of malignancies affecting the bone marrow or blood in al...

Assessment of deep learning algorithms to predict histopathological diagnosis of breast cancer: first Moroccan prospective study on a private dataset.

OBJECTIVE: Breast cancer is a critical public health issue and a leading cause of cancer-related dea...

Segmentation of metastatic cervical lymph nodes from CT images of oral cancers using deep-learning technology.

OBJECTIVE: The purpose of this study was to establish a deep-learning model for segmenting the cervi...

Deep learning driven predictive treatment planning for adaptive radiotherapy of lung cancer.

BACKGROUND AND PURPOSE: To develop a novel deep learning algorithm of sequential analysis, Seq2Seq, ...

Convolutional Blur Attention Network for Cell Nuclei Segmentation.

Accurately segmented nuclei are important, not only for cancer classification, but also for predicti...

An Optimized Framework for Breast Cancer Classification Using Machine Learning.

Breast cancer, if diagnosed and treated early, has a better chance of surviving. Many studies have s...

Interpretable tumor differentiation grade and microsatellite instability recognition in gastric cancer using deep learning.

Gastric cancer possesses great histological and molecular diversity, which creates obstacles for rap...

Solar radiation and solar energy estimation using ANN and Fuzzy logic concept: A comprehensive and systematic study.

To overcome the need of the world for energy consumption, we have to find some better and stable alt...

Machine learning methods to predict presence of residual cancer following hysterectomy.

Surgical management for gynecologic malignancies often involves hysterectomy, often constituting the...

Intravital deep-tumor single-beam 3-photon, 4-photon, and harmonic microscopy.

Three-photon excitation has recently been demonstrated as an effective method to perform intravital ...

Deep Learning Capabilities for the Categorization of Microcalcification.

Breast cancer is the most common cancer in women worldwide. It is the most frequently diagnosed canc...

m6A modification: recent advances, anticancer targeted drug discovery and beyond.

Abnormal N6-methyladenosine (m6A) modification is closely associated with the occurrence, developmen...

A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions.

BACKGROUND: For patients with meningioma, surgical procedures are different because of the status of...

Robot-assisted Total Mesorectal Excision and Lateral Pelvic Lymph Node Dissection for Locally Advanced Middle-low Rectal Cancer.

Since their approval for clinical use, da Vinci surgical robots have shown great advantages in gastr...

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