Lung Cancer

Deep learning-based classification of breast cancer cells using transmembrane receptor dynamics.

MOTIVATION: Motions of transmembrane receptors on cancer cell surfaces can reveal biophysical features of the cancer cells, thus providing a method for characterizing cancer cell phenotypes. While conventional analysis of receptor motions in the cell membrane mostly relies on the mean-squared displacement plots, much information is lost when producing these plots from the trajectories. Here we emp...

[Robot Assisted Lower Anterior Resection for Anastomotic Recurrence of Colorectal Cancer-A Case Report].

Patient undergoing R0 resection have the good survival advantage following surgery for recurrent rectal cancer. Robotic surgery for anastomotic local recurrence of rectal cancer has never been reported before. An 80-year-old woman who had undergone high anterior resection for rectal cancer 1 years previously got colonoscopy. It revealed a 10 mm sized, elevated lesion on the anastomotic site, and a...

Efficacy and safety of carboplatin with nab-paclitaxel versus docetaxel in older patients with squamous non-small-cell lung cancer (CAPITAL): a randomised, multicentre, open-label, phase 3 trial.

BACKGROUND: In Japan, docetaxel, a cytotoxic monotherapy, is the standard drug administered to older patients with advanced non-small-cell lung cancer...

Robotics, imaging, and artificial intelligence in the catheterisation laboratory.

The catheterisation laboratory today combines diagnosis and therapeutics, through various imaging modalities and a prolific list of interventional too...

Automatic contour segmentation of cervical cancer using artificial intelligence.

In cervical cancer treatment, radiation therapy is selected based on the degree of tumor progression, and radiation oncologists are required to deline...

Machine Learning for Early Lung Cancer Identification Using Routine Clinical and Laboratory Data.

Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and impr...

Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning.

Thyroid nodules are neoplasms commonly found among adults, with papillary thyroid carcinoma (PTC) being the most prevalent malignancy. However, curren...

Artificial Intelligence in Diagnostic Imaging and Radiation Therapy.

Artificial intelligence (AI) is a rapidly growing profession that shows continued promise for diagnostic imaging in various disciplines, including der...

Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images.

BACKGROUND: Currently, only a fraction of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) experience...

The potential for reduced radiation dose from deep learning-based CT image reconstruction: A comparison with filtered back projection and hybrid iterative reconstruction using a phantom.

The purpose of this phantom study is to compare radiation dose and image quality of abdominal computed tomography (CT) scanned with different tube vol...

Robotic Radical Cystectomy Outcomes after Intervention for Prostate Cancer.

We evaluated patients who underwent treatment for prostate cancer and then subsequent robot-assisted radical cystectomy (RARC). Our objective was to ...

[A Case of Robot-Assisted Radical Cystoprostatectomy for Locally Advanced Prostate Cancer with Bladder Infiltration].

While robot-assisted radical cystoprostatectomy (RARC) for locally advanced prostate cancer (LAPC) may sometimes prove to be excessive treatment, it c...

[Clinical outcomes for young patients with muscular invasive bladder cancer who received robot-assisted radical cystectomy].

To evaluate the clinical features, surgical effects and factors that may affect prognosis of muscular invasive bladder cancer in young people. The c...

[Preliminary application and efficacy analysis of transumbilical single-incision plus one port robotic total mesorectal excision].

To investigate the feasibility of transumbilical single-incision plus one port (SIPOP) robotic total mesorectal excision. Clinical data of a 70-year...

Verification and comparison of three prediction models of ischemic stroke in young adults based on the back propagation neural networks.

This work aims to explore risk factors for ischemic stroke in young adults and analyze the Traditional Vascular Risk Factors Model based on age, hyper...

Automated approach for segmenting gross tumor volumes for lung cancer stereotactic body radiation therapy using CT-based dense V-networks.

The aim of this study was to develop an automated segmentation approach for small gross tumor volumes (GTVs) in 3D planning computed tomography (CT) i...

Feasibility Study on Automatic Interpretation of Radiation Dose Using Deep Learning Technique for Dicentric Chromosome Assay.

The interpretation of radiation dose is an important procedure for both radiological operators and persons who are exposed to background or artificial...

Deep learning for in vivo near-infrared imaging.

Detecting fluorescence in the second near-infrared window (NIR-II) up to ∼1,700 nm has emerged as a novel in vivo imaging modality with high spatial a...

Differentiation of rare brain tumors through unsupervised machine learning: Clinical significance of in-depth methylation and copy number profiling illustrated through an unusual case of IDH wildtype glioblastoma.

Methylation profiling has become a mainstay in brain tumor diagnostics since the introduction of the first publicly available classification tool by t...

CT Dosimetry: What Has Been Achieved and What Remains to Be Done.

Radiation dose in computed tomography (CT) has become a hot topic due to an upward trend in the number of CT procedures worldwide and the relatively h...