Oncology/Hematology

Lung Cancer

Latest AI and machine learning research in lung cancer for healthcare professionals.

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The integrative knowledge base for miRNA-mRNA expression in colorectal cancer.

"miRNA colorectal cancer" (https://mirna-coadread.omics.si/) is a freely available web application f...

The role of artificial intelligence in medical imaging research.

Without doubt, artificial intelligence (AI) is the most discussed topic today in medical imaging res...

Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer.

BACKGROUND: Accurate and standardized descriptions of organs at risk (OARs) are essential in radiati...

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer.

Artificial intelligence demonstrated its value for automated contouring of organs at risk and target...

Isolated Hepatic Metastasis of Prostate Cancer with Variable F-fluociclovine Uptake by PET/CT Imaging.

A 74-year-old man presented with rapid rising prostate-specific antigen (PSA) 2 years after treatmen...

ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network.

BACKGROUND: The spatial distributions of different types of cells could reveal a cancer cell's growt...

Deep segmentation networks predict survival of non-small cell lung cancer.

Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is t...

Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands.

Wetlands are extraordinary ecosystems and important climate regulators that also contribute to reduc...

Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.

PURPOSE: Acute ischemic stroke is one of the most causes of death all over the world. Onset to treat...

Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.

Tomographic imaging using penetrating waves generates cross-sectional views of the internal anatomy ...

Identification of genes of four malignant tumors and a novel prediction model development based on PPI data and support vector machines.

Triple-negative breast cancer (TNBC), colon adenocarcinoma (COAD), ovarian cancer (OV), and glioblas...

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

INTRODUCTION: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiothe...

Preparing for Artificial Intelligence: Systems-Level Implications for the Medical Imaging and Radiation Therapy Professions.

Innovations in artificial intelligence (AI) are driving a new industrial revolution, and as a result...

[Basis and perspectives of artificial intelligence in radiation therapy].

Artificial intelligence is a highly polysemic term. In computer science, with the objective of being...

A Super-Learner Model for Tumor Motion Prediction and Management in Radiation Therapy: Development and Feasibility Evaluation.

In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumo...

Outpatient Anesthesia Facilitates Stereotactic Body Radiation Therapy for Early Stage Lung Cancer Patients With Advanced Cognitive Impairments.

PURPOSE: To report on the use of outpatient anesthesia (OPA) facilitating delivery of stereotactic b...

Artificial Intelligence and the Medical Radiation Profession: How Our Advocacy Must Inform Future Practice.

There is no escaping the fact that academics are devoting unrelenting attention to the impact artifi...

Two stage residual CNN for texture denoising and structure enhancement on low dose CT image.

BACKGROUND AND OBJECTIVE: X-ray computed tomography (CT) plays an important role in modern medical s...

Optimizing robot motion for robotic ultrasound-guided radiation therapy.

An important aspect of robotic radiation therapy is active compensation of target motion. Recently, ...

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