Oncology/Hematology

Deep learning-based AI model for signet-ring cell carcinoma diagnosis and chemotherapy response prediction in gastric cancer.

PURPOSE: We aimed to develop a noninvasive artificial intelligence (AI) model to diagnose signet-rin...

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC.

Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous can...

Update to improve reproducibility and interpretability: A response to "Machine Learning for Tumor Growth Inhibition".

Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.

BACKGROUND: The evaluation of automatic segmentation algorithms is commonly performed using geometri...

Application of Artificial Intelligence Nuclear Medicine Automated Images Based on Deep Learning in Tumor Diagnosis.

In order to correctly obtain normal tissues and organs and tumor lesions, the research on multimodal...

Interpretable Model Based on Pyramid Scene Parsing Features for Brain Tumor MRI Image Segmentation.

Due to the black box model nature of convolutional neural networks, computer-aided diagnosis methods...

BID-Net: An Automated System for Bone Invasion Detection Occurring at Stage T4 in Oral Squamous Carcinoma Using Deep Learning.

Detection of the presence and absence of bone invasion by the tumor in oral squamous cell carcinoma ...

Low-radiation dose scan protocol for preoperative imaging for dental implant surgery using deep learning-based reconstruction in multidetector CT.

OBJECTIVES: This study aimed to investigate the impact of a deep learning-based reconstruction (DLR)...

Deep learning analysis of contrast-enhanced spectral mammography to determine histoprognostic factors of malignant breast tumours.

OBJECTIVE: To evaluate if a deep learning model can be used to characterise breast cancers on contra...

Brain tumor segmentation in MRI images using nonparametric localization and enhancement methods with U-net.

PURPOSE: Segmentation is one of the critical steps in analyzing medical images since it provides mea...

Using deep learning models to analyze the cerebral edema complication caused by radiotherapy in patients with intracranial tumor.

Using deep learning models to analyze patients with intracranial tumors, to study the image segmenta...

Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer.

Globally with over 10 million deaths per year, cancer is the most transversal disease across countri...

Development of a deep learning-based patient-specific target contour prediction model for markerless tumor positioning.

PURPOSE: For pancreatic cancer patients, image guided radiation therapy and real-time tumor tracking...

Disease-Specific Imaging Utilizing Support Vector Machine Classification of H-Scan Parameters: Assessment of Steatosis in a Rat Model.

In medical imaging, quantitative measurements have shown promise in identifying diseases by classify...

Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach.

Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally. Breas...

WBC-AMNet: Automatic classification of WBC images using deep feature fusion network based on focalized attention mechanism.

The recognition and classification of White Blood Cell (WBC) play a remarkable role in blood-related...

A deep learning model for breast ductal carcinoma in situ classification in whole slide images.

The pathological differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive ...

Extent of pelvic lymph node dissection improves early oncological outcomes for patients with high-risk prostate cancer without lymph node involvement after robot-assisted radical prostatectomy.

BACKGROUND: We investigated the effect of the extent of pelvic lymph node dissection (LND) on bioche...

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer's Disease.

Alzheimer's disease (AD) is the leading cause of age-related dementia, affecting over 5 million peop...

Malignancy risk stratification of cystic renal lesions based on a contrast-enhanced CT-based machine learning model and a clinical decision algorithm.

OBJECTIVE: To distinguish benign from malignant cystic renal lesions (CRL) using a contrast-enhanced...

Palliative Care Exposure Relative to Predicted Risk of Six-Month Mortality in Hospitalized Adults.

CONTEXT: The optimal strategy for implementing mortality-predicting algorithms to facilitate clinica...