Oncology/Hematology

Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.

Liposome-based anticancer agents take advantage of the increased vascular permeability and transvascular pressure gradients for selective accumulation in tumors, a phenomenon known as the enhanced permeability and retention(EPR) effect. The EPR effect has motivated the clinical use of nano-therapeutics, with mixed results on treatment outcome. High interstitial fluid pressure (IFP) has been shown ...

Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence.

Non-Small cell lung cancer (NSCLC) is one of the most dangerous cancers, with 85% of all new lung cancer diagnoses and a 30-55% of recurrence rate after surgery. Thus, an accurate prediction of recurrence risk in NSCLC patients during diagnosis could be essential to drive targeted therapies preventing either overtreatment or undertreatment of cancer patients. The radiomic analysis of CT images has...

Deep learning approaches for differentiating thyroid nodules with calcification: a two-center study.

BACKGROUND: Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification rem...

A narrative review of digital biomarkers in the management of major depressive disorder and treatment-resistant forms.

INTRODUCTION: Depression is the leading cause of worldwide disability, until now only 3% of patients with major depressive disorder (MDD) experiences ...

Accuracy of ChatGPT in head and neck oncological board decisions: preliminary findings.

OBJECTIVES: To evaluate the ChatGPT-4 performance in oncological board decisions.

Performance Analysis in Children of Traditional and Deep Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults.

Although primary lung cancer is rare in children, chest CT is commonly performed to assess for lung metastases in children with cancer. Lung nodule c...

Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer.

BACKGROUND AND OBJECTIVE: Recently, deep learning (DL) algorithms showed to be promising in predicting outcomes such as distant metastasis-free surviv...

Application of CT and MRI images based on an artificial intelligence algorithm for predicting lymph node metastasis in breast cancer patients: a meta-analysis.

BACKGROUND: This study aimed to comprehensively evaluate the accuracy and effect of computed tomography (CT) and magnetic resonance imaging (MRI) base...

Advances in melanoma: epidemiology, diagnosis, and prognosis.

Unraveling the multidimensional complexities of melanoma has required concerted efforts by dedicated community of researchers and clinicians battling ...

Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT.

OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a tr...

"You Are Not Alone": The Allure and Limitations of Artificial Intelligence in Serious Illness Communication.

Artificial intelligence (AI) is changing the way clinicians practice medicine, and recent technological advancements have resulted in consumer-facing ...

[Multistain deep learning as a prognostic and predictive biomarker in colorectal cancer].

The tumor immune microenvironment (TIME) plays a crucial prognostic and predictive role in solid malignancies such as colorectal cancer (CRC). Neverth...

Shedding Light on Colorectal Cancer: An In Vivo Raman Spectroscopy Approach Combined with Deep Learning Analysis.

Raman spectroscopy has emerged as a powerful tool in medical, biochemical, and biological research with high specificity, sensitivity, and spatial and...

Label-Free CD34+ Cell Identification Using Deep Learning and Lens-Free Shadow Imaging Technology.

Accurate and efficient classification and quantification of CD34+ cells are essential for the diagnosis and monitoring of leukemia. Current methods, s...

Hot topics in allergen immunotherapy, 2023: Current status and future perspective.

The importance of allergen immunotherapy (AIT) is multifaceted, encompassing both clinical and quality-of-life improvements and cost-effectiveness in ...

ENAS-B: Combining ENAS With Bayesian Optimization for Automatic Design of Optimal CNN Architectures for Breast Lesion Classification From Ultrasound Images.

Efficient Neural Architecture Search (ENAS) is a recent development in searching for optimal cell structures for Convolutional Neural Network (CNN) de...

Large-scale pancreatic cancer detection via non-contrast CT and deep learning.

Pancreatic ductal adenocarcinoma (PDAC), the most deadly solid malignancy, is typically detected late and at an inoperable stage. Early or incidental ...

Cytotoxic activity of ethyl acetate extract of on MCF7 and T47D breast cancer cells.

One of the most cancers in women that can be fatal is breast cancer. Radiation therapy, chemotherapy, or a combination of the two are often used to tr...

Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers.

Gynecological cancers including breast, cervical, ovarian, uterine, and vaginal, pose the greatest threat to world health, with early identification b...

An attention 3DUNET and visual geometry group-19 based deep neural network for brain tumor segmentation and classification from MRI.

There has been an abrupt increase in brain tumor (BT) related medical cases during the past ten years. The tenth most typical type of tumor affecting ...