Prospective assessment of breast lesions AI classification model based on ultrasound dynamic videos and ACR BI-RADS characteristics.

Introduction: AI-assisted ultrasound diagnosis is considered a fast and accurate new method that can reduce the subjective and experience-dependent nature of handheld ultrasound. In order to meet clinical diagnostic needs better, we first proposed a breast lesions AI classification model based on ultrasound dynamic videos and ACR BI-RADS characteristics (hereafter, Auto BI-RADS). In this study, we prospectively verify its performance.

Enhanced high-temperature electrochemical properties of carbon-coated truncated octahedral LiMnO cathodes.

Truncated octahedral spinel LiMnO was homogenously coated by amorphous carbon layer chemical vapor deposition (CVD) using acetylene gas (CH) as carbon source to ease Mn dissolution to improve high-temperature performance, delivering a capacity retention of 92.9% after 1000 cycles at 5C at 50 °C.

Steric-hindrance effect and self-sacrificing template behavior induced PDA@SnO-QDs/N-doped carbon hollow nanospheres: Enhanced structural stability and reaction kinetics for long-cyclic Li-ion half/full batteries.

Tin-based anode materials with high theoretical specific capacity are subject to huge volume expansion and poor reaction reversibility, leading to degradation of battery performance. Herein, the steric-hindrance effect and self-sacrificing template behavior of polydopamine were firstly developed to induce the formation of hollow nanospheres assembled by ultrafine SnO quantum dots (SnO-QDs) and nitrogen-doped carbon (NC), containing residual polydopamine (PDA) cores. The PDA@SnO-QDs/NC hollow nanospheres could effectively accommodate the volume expansion and maintain structural stability.

Copper Substitution in P2-Type Sodium Layered Oxide To Mitigate Phase Transition and Enhance Cyclability of Sodium-Ion Batteries.

Development of high-performance cathode materials is one of the key challenges in the practical application of sodium-ion batteries. Among all the cathode materials, layered sodium transition-metal oxides are particularly attractive. However, undesired phase transitions are often reported and have detrimental effects on the structure stability and electrochemical performance.

Improved ECG-Derived Respiration Using Empirical Wavelet Transform and Kernel Principal Component Analysis.

Many methods have been developed to derive respiration signals from electrocardiograms (ECGs). However, traditional methods have two main issues: (1) focusing on certain specific morphological characteristics and (2) not considering the nonlinear relationship between ECGs and respiration. In this paper, an improved ECG-derived respiration (EDR) based on empirical wavelet transform (EWT) and kernel principal component analysis (KPCA) is proposed.

Breast ultrasound tumor image classification using image decomposition and fusion based on adaptive multi-model spatial feature fusion.

Background And Objective: Breast cancer is a fatal threat to the health of women. Ultrasonography is a common method for the detection of breast cancer. Computer-aided diagnosis of breast ultrasound images can help doctors in diagnosing benign and malignant lesions.

Multi-Features-Based Automated Breast Tumor Diagnosis Using Ultrasound Image and Support Vector Machine.

Breast ultrasound examination is a routine, fast, and safe method for clinical diagnosis of breast tumors. In this paper, a classification method based on multi-features and support vector machines was proposed for breast tumor diagnosis. Multi-features are composed of characteristic features and deep learning features of breast tumor images.

Automatic Segmentation of Left Ventricle in Echocardiography Based on YOLOv3 Model to Achieve Constraint and Positioning.

Cardiovascular disease (CVD) is the most common type of disease and has a high fatality rate in humans. Early diagnosis is critical for the prognosis of CVD. Before using myocardial tissue strain, strain rate, and other indicators to evaluate and analyze cardiac function, accurate segmentation of the left ventricle (LV) endocardium is vital for ensuring the accuracy of subsequent diagnosis.

Tumor classification in automated breast ultrasound (ABUS) based on a modified extracting feature network.

People can get consistent Automated Breast Ultrasound (ABUS) images due to the imaging mechanism of scanning. Therefore, it has unique advantages in breast tumor classification using artificial intelligence technology. This paper proposes a method for classifying benign and malignant breast tumors using ABUS sequence based on deep learning.

Automatic segmentation for ultrasound image of carotid intimal-media based on improved superpixel generation algorithm and fractal theory.

Objective: Carotid atherosclerosis (CAS) is the main reason leading to cardiovascular conditions such as coronary heart disease and cerebrovascular diseases. In the carotid ultrasound images, the carotid intima-media structure can be observed in an annular narrow strip, which its inner contour corresponds to the carotid intima, and the outer contour corresponds to the carotid extima. With the development of carotid atherosclerosis, the carotid intima-media will gradually thicken.

Effect of pyrolysis condition on the adsorption mechanism of heavy metals on tobacco stem biochar in competitive mode.

To clarify the adsorption mechanism of multi-ions on biochars in competitive environment is very important for the decontamination of co-existed heavy metals. Herein, tobacco stem was pyrolyzed in different temperatures with selected residences to obtain biochars with various surface chemistry. Then the adsorption of co-existed typical heavy-metal ions like lead, cadmium, and copper was studied, followed with systematic analysis of surface properties of the post-adsorption biochars.