Cardiovascular

Cost analysis of implementing a vial-sharing strategy for chemotherapy drugs using intelligent dispensing robots in a tertiary Chinese hospital in Sichuan.

INTRODUCTION: Chemotherapy drug wasting is a huge problem in oncology that not only results in excessive expenses on chemotherapy drugs but also increases the cost of disposing of chemotherapy waste and the risk of occupational exposure in the environment. The main objective of this study was to evaluate the potential for hospitals in China to employ a real-time vial-sharing strategy that can save...

An Intelligent Robot Detection System of Uncontrolled Radioactive Sources.

In recent years, radioactive sources have been widely used in various fields (e.g., nuclear industry, agriculture, medical industry, environmental protection, and scientific research) and successfully applied to develop scientific projects, such as nuclear power generation, sewage treatment, medical diagnosis, and new material development. However, radiation sources continuously got out of control...

Detection of Breast Cancer Lump and BRCA1/2 Genetic Mutation under Deep Learning.

To diagnose and cure breast cancer early, thus reducing the mortality of patients with breast cancer, a method was provided to judge threshold of imag...

Machine Learning approach to Predict net radiation over crop surfaces from global solar radiation and canopy temperature data.

As the ground-based instruments for measuring net radiation are costly and need to be handled skillfully, the net radiation data at spatial and tempor...

Mammogram classification based on a novel convolutional neural network with efficient channel attention.

Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosi...

The three horizons model applied to medical science.

The three horizons model is a framework that helps manage an organization's innovation strategy. This model considers three aspects (horizons) that sh...

Act Like a Radiologist: Towards Reliable Multi-View Correspondence Reasoning for Mammogram Mass Detection.

Mammogram mass detection is crucial for diagnosing and preventing the breast cancers in clinical practice. The complementary effect of multi-view mamm...

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive thera...

Photon-counting Detector CT with Deep Learning Noise Reduction to Detect Multiple Myeloma.

Background Photon-counting detector (PCD) CT and deep learning noise reduction may improve spatial resolution at lower radiation doses compared with e...

Development of GBRT Model as a Novel and Robust Mathematical Model to Predict and Optimize the Solubility of Decitabine as an Anti-Cancer Drug.

The efficient production of solid-dosage oral formulations using eco-friendly supercritical solvents is known as a breakthrough technology towards dev...

Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers.

DNA methylation is a process that can affect gene accessibility and therefore gene expression. In this study, a machine learning pipeline is proposed ...

Predictive modelling for high-risk stage II colon cancer using auto-artificial intelligence.

BACKGROUND: Recently, stratification of high-risk stage II colon cancer (CC) and the need for adjuvant chemotherapy have been the focus of attention. ...

Deep learning method for reducing metal artifacts in dental cone-beam CT using supplementary information from intra-oral scan.

Recently, dental cone-beam computed tomography (CBCT) methods have been improved to significantly reduce radiation dose while maintaining image resolu...

Therapy resistance mechanisms in hematological malignancies.

Hematologic malignancies are model diseases for understanding neoplastic transformation and serve as prototypes for developing effective therapies. In...

mRNAsi-related metabolic risk score model identifies poor prognosis, immunoevasive contexture, and low chemotherapy response in colorectal cancer patients through machine learning.

Colorectal cancer (CRC) is one of the most fatal cancers of the digestive system. Although cancer stem cells and metabolic reprogramming have an impor...

Development of deep learning chest X-ray model for cardiac dose prediction in left-sided breast cancer radiotherapy.

Deep inspiration breath-hold (DIBH) is widely used to reduce the cardiac dose in left-sided breast cancer radiotherapy. This study aimed to develop a ...

Anti-Cancer Drug Solubility Development within a Green Solvent: Design of Novel and Robust Mathematical Models Based on Artificial Intelligence.

Nowadays, supercritical CO(SC-CO) is known as a promising alternative for challengeable organic solvents in the pharmaceutical industry. The mathemati...

A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study.

BACKGROUND: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and w...

Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer.

Deep learning (DL) based approach aims to construct a full workflow solution for cervical cancer with external beam radiation therapy (EBRT) and brach...

Noncirrhotic Portal Hypertension after Trastuzumab Emtansine in HER2-positive Breast Cancer as Determined by Deep Learning-measured Spleen Volume at CT.

Background Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate approved for use in human epidermal growth factor receptor 2 (HER2)-positive br...