Cardiovascular

Artificial intelligence-powered optimization of KI-67 assessment in breast cancer: enhancing precision and workflow efficiency. a literature review.

Breast Cancer (BC) has evolved from traditional morphological analysis to molecular profiling, identifying new subtypes. Ki-67, a prognostic biomarker, helps classify subtypes and guide chemotherapy decisions. This review explores how artificial intelligence (AI) can optimize Ki-67 assessment, improving precision and workflow efficiency in BC management. The study presents a critical analysis of t...

Improving drug response prediction via integrating gene relationships with deep learning.

Predicting the drug response of cancer cell lines is crucial for advancing personalized cancer treatment, yet remains challenging due to tumor heterogeneity and individual diversity. In this study, we present a deep learning-based framework named Deep neural network Integrating Prior Knowledge (DIPK) (DIPK), which adopts self-supervised techniques to integrate multiple valuable information, includ...

Eravacycline, an antibacterial drug, repurposed for pancreatic cancer therapy: insights from a molecular-based deep learning model.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a serious threat to health, with limited effective therapeutic options, especially due to ...

Safety and Feasibility of Single-Port Robotic-Assisted Nipple-Sparing Mastectomy.

IMPORTANCE: Robotic-assisted nipple-sparing mastectomies with multiport robots have been described in the US since 2015; however, significant hurdles ...

[Current status and prospects for the application of robot-assisted spine surgery].

Traditional spine surgery frequently encounters difficulties with inadequate surgical visualization and high risk.Robot-assisted spine surgery is quic...

Deep Learning of Multimodal Ultrasound: Stratifying the Response to Neoadjuvant Chemotherapy in Breast Cancer Before Treatment.

BACKGROUND: Not only should resistance to neoadjuvant chemotherapy (NAC) be considered in patients with breast cancer but also the possibility of achi...

Towards an Explainable AI Platform to Study Interruptions in Cancer Radiation Therapy.

Radiation therapy interruptions drive cancer treatment failures; they represent an untapped opportunity for improving outcomes and narrowing treatment...

Deep learning for automated segmentation in radiotherapy: a narrative review.

The segmentation of organs and structures is a critical component of radiation therapy planning, with manual segmentation being a laborious and time-c...

Integrating AI into Clinical Workflows: A Simulation Study on Implementing AI-aided Same-day Diagnostic Testing Following an Abnormal Screening Mammogram.

Artificial intelligence (AI) shows promise in clinical tasks, yet its integration into workflows remains underexplored. This study proposes an AI-aide...

A Multi-Task Learning Approach for Segmentation of Breast Arterial Calcifications in Screening Mammograms.

Screening mammogram is a standard and cost-efficient imaging procedure to measure breast cancer risk among 45+ year old women. Quantifying breast arte...

Preemptive Forecasting of Symptom Escalation in Cancer Patients Undergoing Chemotherapy.

This study evaluates the utility of machine learning (ML) algorithms in early forecasting of total symptom score changes from daily self-reports of 33...

Artificial Intelligence-suggested Predictive Model of Survival in Patients Treated With Stereotactic Radiotherapy for Early Lung Cancer.

BACKGROUND/AIM: Overall survival (OS)-predictive models to clinically stratify patients with stage I Non-Small Cell Lung Cancer (NSCLC) undergoing ste...

Robot-assisted retroperitoneal lymph node dissection as primary treatment for stage II seminoma germ cell tumor.

INTRODUCTION: Historically, therapeutic avenues for patients with clinical stage II seminoma germ cell tumors (SGCT) were confined to radiotherapy and...

Evaluation of the efficacy and safety of robot-assisted and video assisted thoracic surgery for early non-small cell lung cancer: A meta-analysis.

BACKGROUND: Radical resection of lung cancer and chemotherapy are the main methods for the treatment of early lung cancer, but surgical treatment is s...

The Future of MR-Guided Radiation Therapy.

Magnetic resonance image guided radiation therapy (MRIgRT) is a relatively new technology that has already shown outcomes benefits but that has not ye...

Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography.

PURPOSE: The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesi...

A Comparative Study of Deep Learning Dose Prediction Models for Cervical Cancer Volumetric Modulated Arc Therapy.

Deep learning (DL) is widely used in dose prediction for radiation oncology, multiple DL techniques comparison is often lacking in the literature. To...

Convolutional Neural Networks for Glioma Segmentation and Prognosis: A Systematic Review.

Deep learning (DL) is poised to redefine the way medical images are processed and analyzed. Convolutional neural networks (CNNs), a specific type of D...

Deep-Learning Model Prediction of Radiation Pneumonitis Using Pretreatment Chest Computed Tomography and Clinical Factors.

This study aimed to build a comprehensive deep-learning model for the prediction of radiation pneumonitis using chest computed tomography (CT), clini...

Breast Mass Detection and Classification Using Machine Learning Approaches on Two-Dimensional Mammogram: A Review.

Breast cancer is a leading cause of mortality among women, both in India and globally. The prevalence of breast masses is notably common in women aged...