AIMC Topic: Female

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A hybrid deep learning model for breast cancer diagnosis based on transfer learning and pulse-coupled neural networks.

Mathematical biosciences and engineering : MBE
Radiology experts often face difficulties in mammography mass lesion labeling, which may lead to conclusive yet unnecessary and expensive breast biopsies. This paper focuses on building an automated diagnosis tool that supports radiologists in identi...

Discovery of molecular features underlying the morphological landscape by integrating spatial transcriptomic data with deep features of tissue images.

Nucleic acids research
Profiling molecular features associated with the morphological landscape of tissue is crucial for investigating the structural and spatial patterns that underlie the biological function of tissues. In this study, we present a new method, spatial gene...

A convolutional neural network algorithm for breast tumor detection with magnetic detection electrical impedance tomography.

The Review of scientific instruments
Breast cancer is a malignant tumor disease for which early detection, diagnosis, and treatment are of paramount significance in prolonging the life of patients. Magnetic Detection Electrical Impedance Tomography (MDEIT) based on the Convolutional Neu...

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

Journal for immunotherapy of cancer
BACKGROUND: Currently, only a fraction of patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) experience a durable clinical benefit (DCB). According to NCCN guidelines, Programmed death-ligand 1 (PD-L1) e...

[Robot-assisted nephroureterectomy requiring no robot redocking or patient repositioning: experience from a single center with 62 cases].

Zhonghua wai ke za zhi [Chinese journal of surgery]
To examine a new technique of robot-assisted nephroureterectomy without robot reldocking or patient repositioning. Patients diagnosed as upper tract urothelial carcinoma treated with this modality between November 2015 and January 2019 at Departmen...

Fully automatic segmentation of sinonasal cavity and pharyngeal airway based on convolutional neural networks.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: This study aimed to test the accuracy of a new automatic deep learning-based approach on the basis of convolutional neural networks (CNN) for fully automatic segmentation of the sinonasal cavity and the pharyngeal airway from cone-beam ...

Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study.

The Lancet. Digital health
BACKGROUND: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heteroge...

Development of a field artificial intelligence triage tool: Confidence in the prediction of shock, transfusion, and definitive surgical therapy in patients with truncal gunshot wounds.

The journal of trauma and acute care surgery
BACKGROUND: In-field triage tools for trauma patients are limited by availability of information, linear risk classification, and a lack of confidence reporting. We therefore set out to develop and test a machine learning algorithm that can overcome ...

Use of Machine Learning Models to Predict Death After Acute Myocardial Infarction.

JAMA cardiology
IMPORTANCE: Accurate prediction of adverse outcomes after acute myocardial infarction (AMI) can guide the triage of care services and shared decision-making, and novel methods hold promise for using existing data to generate additional insights.

Utility of a Deep-Learning Algorithm to Guide Novices to Acquire Echocardiograms for Limited Diagnostic Use.

JAMA cardiology
IMPORTANCE: Artificial intelligence (AI) has been applied to analysis of medical imaging in recent years, but AI to guide the acquisition of ultrasonography images is a novel area of investigation. A novel deep-learning (DL) algorithm, trained on mor...