Latest AI and machine learning research in anemia for healthcare professionals.
BACKGROUND: According to the WHO, anemia is a highly prevalent disease, especially for patients in t...
Coronavirus disease 2019 (COVID-19) continues to be a disease of global importance, with an increasi...
It is of great practical and theoretical significance to identify driver fatigue state in real time ...
Sickle Cell Anemia (SCA) is a disorder in Red Blood Cells (RBCs) of human blood. Children under five...
BACKGROUND: More than 115,000 maternal deaths and 591,000 prenatal deaths occurred in the world per ...
Label noise is omnipresent in the annotations process and has an impact on supervised learning algor...
Around 60-80% of radiological errors are attributed to overlooked abnormalities, the rate of which i...
Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledg...
Measuring trust is an important element of effective human-robot collaborations (HRCs). It has large...
This pilot study aimed to assess the safety and feasibility of an EMG-driven rehabilitation robot in...
The growth and implementation of biofuels and bioenergy conversion technologies play an important pa...
Among the IL-6 inhibitors, tocilizumab is the most widely used therapeutic option in patients with S...
In computational biology, the Protein Remote homology Detection technique (PRHD) has got undeniable ...
BACKGROUND: The ability of endoscopists to identify gastric lesions is uneven. Even experienced endo...
After an attack of pancreatitis, individuals may develop metabolic sequelae (eg, new-onset diabetes)...
The insulated gate bipolar transistor (IGBT) is widely utilized in the transportation, power, and en...
Blood pressure (BP) is a basic determinant for organ blood flow supply. Insufficient blood supply wi...
Recently, the novel coronavirus disease 2019 (COVID-19) has posed many challenges to the research co...
In this paper, the algorithm of the deep convolutional neural network is used to conduct in-depth re...
OBJECTIVES: To identify the feasibility of deep learning-based diagnostic models for detecting and a...
BACKGROUND: Remote surgery social implementation necessitates achieving low latency and highly relia...