Latest AI and machine learning research in alternative medicine for healthcare professionals.
This study aimed to assess the diagnostic performance of deep convolutional neural networks (DCNNs) in classifying breast microcalcification in screening mammograms. To this end, 1579 mammographic images were collected retrospectively from patients exhibiting suspicious microcalcification in screening mammograms between July 2007 and December 2019. Five pre-trained DCNN models and an ensemble mode...
This research evaluates the effect on herbal crops of mechanical stress induced by two specially developed robotic platforms. The changes in plant morphology, metabolite profiles, and element content are evaluated in a series of three empirical experiments, conducted in greenhouse and CNC growing bed conditions, for the case of basil plant growth. Results show significant changes in morphological ...
Machine learning (ML), as a branch of artificial intelligence, acquires the potential and meaningful rules from the mass of data via diverse algorithm...
The spread of different types of cancer has been on a rise in the recent century. The use of chemical medications develops drug resistance and causes ...
This study presents a method with high accuracy performance that aims to automatically detect schizophrenia (SZ) from electroencephalography (EEG) rec...
With the development in the field of neural networks,(XAI), is being studied to ensure that artificial intelligence models can be explained. There are...
Chest X-ray image is an important clinical diagnostic reference to lung diseases that is a serious threat to human health. At present, with the rapid ...
Electron portable Raman spectroscopy tools for ore mineral identification are widely used in raw ore analysis and mineral process engineering. This pa...
Artificial intelligence (AI) comprises a wide range of technologies and methods with heterogeneous degrees of complexity, applications, and abilities....
COVID-19 is a sort of infectious disease caused by a new strain of coronavirus. This study aims to develop a more accurate COVID-19 diagnosis system....
In order to discuss the clinical characteristics of patients with scapular fracture, deep learning model was adopted in ultrasound images of patients ...
The concentration of soluble salts in surface water and rivers such as sodium, sulfate, chloride, magnesium ions, etc., plays an important role in the...
BACKGROUND: True evidence-informed decision-making in public health relies on incorporating evidence from a number of sources in addition to tradition...
An aging population and technology are two rapidly evolving phenomena occurring simultaneously worldwide. To examine the literature on the acceptabili...
The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by thi...
Innovations in health care are growing exponentially, resulting in improved quality of and access to care, as well as rising societal costs of care an...
Deep convolutional neural network (DCNN) has proved to be a promising tool for identifying organic chemicals of environmental concern. However, the un...
We propose an interpretable and lightweight 3D deep neural network model that diagnoses anterior cruciate ligament (ACL) tears from a knee MRI exam. P...
A growing body of evidence currently proposes that deep learning approaches can serve as an essential cornerstone for the diagnosis and prediction of ...
The recent deluge of genome-wide technologies for the mapping of the epigenome and resulting data in cancer samples has provided the opportunity for g...