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Jammu Kashmir, India, Asia, Algorithms, Cancer, Cervical Cancer, Diagnostics and Screening, Health and Medicine, Oncology, Women's Health Keywords: Jammu Kashmir; India; Asia; Algorithms; Cancer; Cervical Cancer; Diagnostics and Screening; Health and Medicine; Oncology; Women's Health EN Jammu Kashmir India Asia Algorithms Cancer Cervical Cancer Diagnostics and Screening Health and Medicine Oncology Women's Health 1014 1014 1 10/03/23 20231006 NES 231006 2023 OCT 3 (NewsRx) -- By a News Reporter-Staff News Editor at Women's Health Weekly -- A new study on Oncology - Cervical Cancer is now available. [Extracted from the article]

Most of the existing studies around breast cancer classification adopt a single algorithm to fit breast cancer data but ignore the applicability of different breast cancer data features to the model. Keywords: Algorithms; Breast Cancer; Cancer; Cyborgs; Diagnostics and Screening; Emerging Technologies; Health and Medicine; Machine Learning; Oncology; Women's Health EN Algorithms Breast Cancer Cancer Cyborgs Diagnostics and Screening Emerging Technologies Health and Medicine Machine Learning Oncology Women's Health 471 471 1 03/23/23 20230324 NES 230324 2023 MAR 21 (NewsRx) -- By a News Reporter-Staff News Editor at Women's Health Weekly -- Current study results on breast cancer have been published. [Extracted from the article]

A recent study conducted by researchers at the First Affiliated Hospital of Wenzhou Medical University in China explores the use of deep learning algorithms in medical image analysis. The study highlights the importance of employing advanced deep learning techniques in this field, as they have shown impressive results in various areas of healthcare. The researchers categorized and assessed different deep learning techniques, such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), based on their principles, advantages, limitations, methodologies, and datasets. The study also addresses the challenges that hinder the widespread implementation of deep learning in medical image analysis. The findings of this research provide valuable insights for future studies and advancements in image analysis in medical healthcare research. [Extracted from the article]

A recent study conducted by researchers from the Icahn School of Medicine at Mount Sinai in New York City explores the use of advanced deep learning algorithms for magnetic resonance imaging (MRI) segmentation. Accurate MRI segmentation is crucial for diagnosing abnormalities and planning treatments, but traditional supervised learning techniques require a large amount of annotated data. The study reviews state-of-the-art algorithms that utilize a limited number of annotated samples, including self-supervised learning, generative models, few-shot learning, and semi-supervised learning. The researchers also discuss future directions in the field, such as contrastive language-image pretraining, to further improve image segmentation with limited labels. [Extracted from the article]

A researcher from the University of Science and Technology Beijing has conducted a study on the predictive analysis of brain imaging data using deep learning algorithms. The study aimed to improve the accuracy and efficiency of brain imaging data prediction. The researcher developed a batch normalized convolutional neural network (BN-CNN) based prediction method, which showed promising results in predicting missing structural data in brain imaging. The algorithm was applied to epilepsy and Parkinson's cases, achieving an average prediction accuracy of 93.37%. The study suggests that deep learning algorithms have the potential to greatly benefit clinical diagnosis and treatment in the future. [Extracted from the article]

Researchers from the University of Dhaka in Bangladesh have conducted a review of machine learning and deep learning algorithms for the detection of Parkinson's disease (PD) using handwriting and voice datasets. The study highlights the potential of these techniques in improving diagnostic accuracy and aiding clinical decision-making. The research serves as a roadmap for future studies in the development of ML and DL-based tools for PD detection, with the aim of advancing understanding and improving patient outcomes. This information is valuable for the scientific community and medical practitioners interested in personalized medicine and emerging technologies. [Extracted from the article]

Researchers from UCSI University in Kuala Lumpur, Malaysia have published a report on optical character recognition (OCR), which is the process of extracting and processing text from images. The report highlights the challenges faced during the OCR process, including font properties and image quality. The researchers propose an improved algorithm for OCR using graphical user interface design, which can be used with deep learning software for robotic and AI applications. This research provides valuable insights into the development of OCR technology. [Extracted from the article]

A recent report from Federal University Maranhao explores the use of machine learning and deep learning algorithms in the aviation industry. The study focuses on aircraft diagnosis/prognosis, predictive maintenance, feature selection, and flight data monitoring. The research highlights the potential benefits of these algorithms in enhancing aircraft operations, such as defect identification, calculation of remaining usable life, and prediction of excessive vibration in aero-engines. The application of machine learning algorithms in predictive maintenance allows for real-time assessment of equipment health, reducing hazards and improving overall performance. Flight data monitoring is also emphasized as a crucial aspect of improving safety and operational efficiency in civil aviation. [Extracted from the article]

Researchers at the University of Campania Luigi Vanvitelli in Italy have conducted a study on machine learning algorithms in the context of diabetes management. The aim of the study was to understand the characteristics and practical implications of these algorithms, specifically in predicting blood glucose levels. The researchers explored and compared different machine learning techniques, with a focus on deep learning techniques such as Long Short-Term Memory Networks. The study investigated the trade-off between accuracy, resource utilization, time consumption, and computational power requirements to identify the optimal balance. The research concluded that the algorithms exhibited distinct behaviors and highlighted their differences, even when their analytical underpinnings appeared similar. [Extracted from the article]

Tamil Nadu, India, Asia, Algorithms, Cancer, Cancer Detection, Cyborgs, Emerging Technologies, Health and Medicine, Machine Learning, Oncology, Skin Cancer, Skin Neoplasms Keywords: Tamil Nadu; India; Asia; Algorithms; Cancer; Cancer Detection; Cyborgs; Emerging Technologies; Health and Medicine; Machine Learning; Oncology; Skin Cancer; Skin Neoplasms EN Tamil Nadu India Asia Algorithms Cancer Cancer Detection Cyborgs Emerging Technologies Health and Medicine Machine Learning Oncology Skin Cancer Skin Neoplasms 732 732 1 09/19/23 20230919 NES 230919 2023 SEP 19 (NewsRx) -- By a News Reporter-Staff News Editor at Clinical Oncology Week -- Investigators publish new report on Oncology - Cancer Detection. [Extracted from the article]

Keywords: Algorithms; Diagnostics; Diagnostics and Screening; Health and Medicine; Networks; Neural Networks EN Algorithms Diagnostics Diagnostics and Screening Health and Medicine Networks Neural Networks 355 355 1 07/03/23 20230706 NES 230706 2023 JUL 6 (NewsRx) -- By a News Reporter-Staff News Editor at Blood Weekly -- Investigators publish new report on diagnostics. Algorithms, Diagnostics, Diagnostics and Screening, Health and Medicine, Networks, Neural Networks. [Extracted from the article]

Keywords: Algorithms; Cardiology; Cardiovascular; Cardiovascular Diseases and Conditions; Cardiovascular Research; Cyborgs; Emerging Technologies; Health and Medicine; Machine Learning; Risk and Prevention EN Algorithms Cardiology Cardiovascular Cardiovascular Diseases and Conditions Cardiovascular Research Cyborgs Emerging Technologies Health and Medicine Machine Learning Risk and Prevention 873 873 1 06/26/23 20230626 NES 230626 2023 JUN 26 (NewsRx) -- By a News Reporter-Staff News Editor at Cardiovascular Week -- Current study results on cardiovascular diseases and conditions have been published. Several ML and DL algorithms are useful for predicting cardiovascular diseases. [Extracted from the article]

Algorithms, Cancer, Colon Cancer, Colorectal Research, Gastroenterology, Health and Medicine, Oncology Keywords: Algorithms; Cancer; Colon Cancer; Colorectal Research; Gastroenterology; Health and Medicine; Oncology EN Algorithms Cancer Colon Cancer Colorectal Research Gastroenterology Health and Medicine Oncology 273 273 1 05/02/23 20230502 NES 230502 2023 MAY 2 (NewsRx) -- By a News Reporter-Staff News Editor at Cancer Weekly -- Fresh data on colon cancer are presented in a new report. [Extracted from the article]

A study conducted by researchers at the University of Health Sciences in Adana, Turkey, has developed a deep machine learning algorithm to diagnose thyroid cancer. The algorithm addresses the challenges of multi-dimensional big data and randomly distributed missing data, which are common in thyroid cancer diagnoses. The algorithm achieved 100% training and 83% testing preciseness for unseen data, and its computational time efficiency was also examined. This research provides valuable insights into the use of machine learning in diagnosing thyroid cancer. [Extracted from the article]

Researchers at SRM Institute of Science and Technology in Tamil Nadu, India, have developed hybrid deep learning algorithms to detect stress and anxiety-based seizures in individuals with epilepsy. The algorithms analyze electroencephalography (EEG) signals and synthesize seizures of different sizes and shapes based on stress and anxiety levels. The proposed methods, FCM-PSO-LSTM and PSO-LSTM, demonstrated high accuracy in the early detection of stress and anxiety-based seizures. This research provides valuable insights into improving the diagnosis and treatment of anxiety disorders in individuals with epilepsy. [Extracted from the article]

A study conducted by the College of Computer Science and Engineering explores the use of machine learning algorithms (MLAs) for the classification of sleep disorders. The study compares deep learning algorithms and conventional MLAs and proposes an optimized method for sleep disorder classification. The results show that the artificial neural network (ANN) algorithm achieved the highest classification accuracy of 92.92%. This research provides valuable insights into the potential of MLAs in improving the accuracy of sleep disorder classification, which can have a significant impact on human health and quality of life. [Extracted from the article]

A recent report from Capital Medical University in Beijing, China discusses the use of neuroimaging technology in diagnosing brain diseases. The researchers developed a deep neural network imaging technology based on the deep learning algorithms of neural imaging techniques. They used this technology to solve binary classification problems related to Alzheimer's disease and Mild Cognitive Impairment. The results showed that the deep neural network with stack auto-encoder feature extraction performed better than other methods, with an accuracy rate of 74.9%. This research provides valuable insights into the potential of deep learning algorithms in diagnosing brain diseases. [Extracted from the article]

A report from Concordia University in Montreal, Canada discusses the use of deep learning algorithms in stock portfolio selection and predictions. The researchers use genetic algorithms to optimize the hyperparameters of deep learning models and compare the results to a random-grid search. The study finds that the genetic algorithm brings a 40% improvement in prediction accuracy and shows promising portfolio returns that are 20% better than the general market. The research integrates various techniques and strategies to enhance the performance of the models. [Extracted from the article]

A new report from the Nanyang Institute of Technology in China discusses the use of a novel deep learning model for electrocardiogram (ECG) classification and arrhythmia detection. The researchers propose an edge-based algorithm that combines continuous wavelet transform (CWT) and short-time Fourier transform (STFT) in a hybrid convolutional neural network (CNN) and Long Short-Term Memory (LSTM) model. The algorithm is trained and evaluated using the MIT-BIH arrhythmia database and optimized for edge computing on a Raspberry Pi device. The proposed classifiers achieve high accuracy and can be used for arrhythmia monitoring on various edge devices. [Extracted from the article]

Researchers from the University of Anbar have developed a deep learning algorithm using EfficientNet B3 for the detection of lung cancer. The algorithm aims to improve detection accuracy and potentially revolutionize medical imaging and patient care. The model was able to classify four different types of lung cancer with an accuracy rate of 96%, showing a 2.13% improvement compared to the best-trained classifier. The researchers believe that this model has the potential to enhance lung cancer detection and support early diagnosis. [Extracted from the article]

Researchers from Shahid Beheshti University of Medical Sciences in Tehran, Iran have developed a deep learning algorithm to enhance the quality of Magnetic Resonance Imaging (MRI) images and generate synthetic Computed Tomography (CT) images for more accurate radiotherapy planning. The study utilized the pix2pix Generative Adversarial Network to synthesize CT images from noisy MRI images of 20 patients with brain disease. The statistical measurements of the synthetic CT images were compared to referenced CT images, and the results showed that the proposed method provides an acceptable level of accuracy for radiotherapy treatment planning. [Extracted from the article]

A recent report discusses the challenges of accurately identifying autism spectrum disorder (ASD) due to its heterogeneity. The report highlights the importance of early diagnosis and intervention for positive treatment outcomes and skill development. The use of artificial intelligence (AI) algorithms, particularly in facial images and MRI scans, has shown promise in detecting ASD. The study presents a comprehensive examination of AI techniques, such as machine learning and deep learning, and their accuracy in identifying ASD in facial and MRI images. The research concludes that deep learning models are highly accurate in ASD detection. [Extracted from the article]

A recent study conducted by researchers from Sichuan University in China explores the use of machine learning and deep learning algorithms in the diagnosis of skin diseases. The study reviews existing research on the topic, focusing on recent advancements in deep learning methods. The findings suggest that deep learning techniques are more effective than traditional machine learning algorithms in dermatological diagnosis, but there is still room for improvement in terms of algorithm accuracy. The study also highlights the need for more diverse datasets and a broader focus on pigmented dermatology research in future studies. [Extracted from the article]

A recent report discusses research conducted at Guangxi University of Chinese Medicine on materials research, specifically focusing on the use of deep learning technology for medical image segmentation. The researchers propose a fuzzy-controlled multicellular gene expression programming algorithm to automatically build and optimize the U-Net network model. The experimental results indicate that this algorithm outperforms other models in image recognition segmentation, particularly in the segmentation of COVID-19 CT medical images. For more information, readers can refer to the article "Fully Automated Construction of a Deep U-net Network Model for Medical Image Segmentation" published in Sensors and Materials. [Extracted from the article]

A new report from researchers at the Ramrao Adik Institute of Technology in Maharashtra, India, explores the integration of machine learning and traditional image processing in dentistry. The study reviews the literature on deep learning and dental radiograph analysis, focusing on applications such as automatic teeth identification and numbering, caries and anomaly detection, disease detection, and dental treatment prediction. The researchers provide an overview of machine learning algorithms in these areas and discuss the available dental radiograph dataset for experiments. The study concludes by highlighting new research opportunities and initiatives in this field, offering a comprehensive overview of the growing area of machine learning in dentistry. [Extracted from the article]

A report from the University Francisco of Vitoria in Madrid, Spain discusses the use of artificial intelligence (AI) in enhancing breast cancer diagnosis. The researchers evaluated different approaches using thermographic imaging and found that a hybrid model of convolutional neural networks and evolutionary algorithms achieved an accuracy of nearly 94%. The study highlights the potential benefits of computer vision and AI in medical diagnosis, particularly in the field of breast cancer screening. The research has been peer-reviewed and provides valuable insights into the application of AI in healthcare. [Extracted from the article]

A new report from researchers at Beijing Normal University at Zhuhai in China explores the application of deep learning algorithms in physics teaching. The study investigates the limitations of traditional physics teaching methods and proposes a physics teaching system based on information big data and data mining technology. The researchers use an artificial neuron model and recurrent neural network, along with an attention mechanism, to improve the generalization performance of the model. Empirical evidence shows that the application of this physics teaching system leads to better learning outcomes compared to traditional teaching methods. [Extracted from the article]

Researchers at People's Hospital in Urumqi, China have developed a new diagnostic technique using porous silicon and deep learning algorithms. The technique, called surface-enhanced Raman spectroscopy (SERS), is a non-invasive and reliable method for disease screening and diagnosis. The researchers created a composite SERS substrate with high sensitivity and stability, and combined it with five deep learning algorithms to construct rapid screening models for immune diseases and chronic kidney disease. The results showed promising classification accuracy rates, suggesting that this technique has potential for non-invasive and rapid clinical diagnosis. [Extracted from the article]

A study conducted by researchers at VIT-AP University in Andhra Pradesh, India, has developed a deep learning algorithm called RU-Net2+ for accurate brain tumor segmentation and survival rate prediction. The algorithm was applied to a dataset of brain tumor images and achieved impressive results, surpassing current benchmarks in classification accuracy, tumor segmentation precision, and survival rate prediction. The framework shows promise for automating brain tumor diagnosis and enhancing patient care, providing valuable insights for medical professionals making treatment decisions. The study was published in IEEE Access. [Extracted from the article]

A study conducted by researchers at Dongguk University in Seoul, South Korea, explores the use of machine learning techniques, specifically deep learning networks (DNNs), in diagnosing COVID-19. The researchers propose a method called the dropout-bagging (DB-COVIDNet) algorithm, which acts as a defense mechanism against poisoning backdoor attacks. The algorithm removes trigger-related features and uses a new voting method to achieve accurate results. The study found that DB-COVIDNet significantly reduces the success rate of backdoor attacks and maintains high accuracy on clean data. The research provides valuable insights into the robustness of DNN-based systems against cyber-security attacks. [Extracted from the article]

Keywords: Algorithms; Life Sciences; Ultrasound EN Algorithms Life Sciences Ultrasound 334 334 1 09/11/23 20230911 NES 230911 2023 SEP 16 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Imaging Week -- Current study results on life sciences have been published. According to the news reporters, the research concluded: "DL techniques show great potential in terms of US images acquired in preclinical studies using animal models. [Extracted from the article]

Keywords: Islamabad; Pakistan; Asia; Mathematics; Algorithms; Health and Medicine; Poisoning EN Islamabad Pakistan Asia Mathematics Algorithms Health and Medicine Poisoning 4158 4158 1 08/07/23 20230811 NES 230811 2023 AUG 11 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Investigators discuss new findings in Mathematics. Islamabad, Pakistan, Asia, Mathematics, Algorithms, Health and Medicine, Poisoning. [Extracted from the article]

Algorithms, Blood Cells, Cell Research, Life Sciences, Medical and Biological Mechanics Keywords: Algorithms; Blood Cells; Cell Research; Life Sciences; Medical and Biological Mechanics EN Algorithms Blood Cells Cell Research Life Sciences Medical and Biological Mechanics 7024 7024 1 08/07/23 20230811 NES 230811 2023 AUG 11 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Research findings on medical and biological mechanics are discussed in a new report. Keywords for this news article include: University of Tlemcen, Algorithms, Blood Cells, Cell Research, Life Sciences, Medical and Biological Mechanics. [Extracted from the article]

Keywords: Chennai; India; Asia; Obesity Fitness and Wellness; Algorithms; Cardiology; Health and Medicine EN Chennai India Asia Obesity Fitness and Wellness Algorithms Cardiology Health and Medicine 571 571 1 08/07/23 20230807 NES 230807 2023 AUG 7 (NewsRx) -- By a News Reporter-Staff News Editor at Cardiovascular Week -- Investigators discuss new findings in Obesity, Fitness and Wellness. Chennai, India, Asia, Obesity Fitness and Wellness, Algorithms, Cardiology, Health and Medicine. [Extracted from the article]

Algorithms, Health and Medicine, Manual Communication, Rehabilitation, Rehabilitation of Hearing Impaired, Sign Language, Therapy Keywords: Algorithms; Health and Medicine; Manual Communication; Rehabilitation; Rehabilitation of Hearing Impaired; Sign Language; Therapy EN Algorithms Health and Medicine Manual Communication Rehabilitation Rehabilitation of Hearing Impaired Sign Language Therapy 7305 7305 1 07/03/23 20230707 NES 230707 2023 JUL 7 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- New research on algorithms is the subject of a new report. [Extracted from the article]

According to the news editors, the research concluded: "The thoracic aortic aneurysm was not concentrated much in the literature review, so the prediction of thoracic aortic aneurysm using machine learning as well as deep learning model is recommended." Tamil Nadu, India, Asia, Algorithms, Aneurysm, Aortic Aneurysm, Aortic Diseases and Conditions, Cardiology, Cardiovascular Diseases and Conditions, Cyborgs, Emerging Technologies, Health and Medicine, Machine Learning, Vascular Diseases and Conditions Keywords: Tamil Nadu; India; Asia; Algorithms; Aneurysm; Aortic Aneurysm; Aortic Diseases and Conditions; Cardiology; Cardiovascular Diseases and Conditions; Cyborgs; Emerging Technologies; Health and Medicine; Machine Learning; Vascular Diseases and Conditions EN Tamil Nadu India Asia Algorithms Aneurysm Aortic Aneurysm Aortic Diseases and Conditions Cardiology Cardiovascular Diseases and Conditions Cyborgs Emerging Technologies Health and Medicine Machine Learning Vascular Diseases and Conditions 1063 1063 1 07/03/23 20230703 NES 230703 2023 JUL 3 (NewsRx) -- By a News Reporter-Staff News Editor at Cardiovascular Week -- Investigators publish new report on Cardiovascular Diseases and Conditions - Aortic Aneurysm. [Extracted from the article]

Madurai, India, Asia, Algorithms, Health and Medicine, Malaria, Mosquito-Borne Diseases, Protozoan Infections Keywords: Madurai; India; Asia; Algorithms; Health and Medicine; Malaria; Mosquito-Borne Diseases; Protozoan Infections EN Madurai India Asia Algorithms Health and Medicine Malaria Mosquito-Borne Diseases Protozoan Infections 13 13 1 07/03/23 20230704 NES 230704 2023 JUL 4 (NewsRx) -- By a News Reporter-Staff News Editor at Zika & Mosquito Week -- Research findings on Mosquito-Borne Diseases - Malaria are discussed in a new report. [Extracted from the article]

Keywords: Kermanshah; Iran; Algorithms; Ant Colony Optimization; Coronaviridae; Coronavirus; Deep Learning; Diagnostics and Screening; Emerging Technologies; Health and Medicine; Machine Learning; Nidovirales; RNA Viruses; Risk and Prevention; Viral; Virology EN Kermanshah Iran Algorithms Ant Colony Optimization Coronaviridae Coronavirus Deep Learning Diagnostics and Screening Emerging Technologies Health and Medicine Machine Learning Nidovirales RNA Viruses Risk and Prevention Viral Virology 987 987 1 06/26/23 20230630 NES 230630 2023 JUL 2 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Letter on the CDC & FDA -- Investigators discuss new findings in RNA Viruses - Coronavirus. The news editors report that additional information may be obtained by contacting Farhad Mardukhi, Razi University, Dept. of Computer Engineering and Information Technology, Kermanshah 9417171946, Iran. [Extracted from the article]

Algorithms, Health and Medicine, Mental Disorders, Mental Health Diseases and Conditions Keywords: Algorithms; Health and Medicine; Mental Disorders; Mental Health Diseases and Conditions EN Algorithms Health and Medicine Mental Disorders Mental Health Diseases and Conditions 412 412 1 06/26/23 20230630 NES 230630 2023 JUN 26 (NewsRx) -- By a News Reporter-Staff News Editor at Mental Health Weekly Digest -- Investigators publish new report on mental disorders. Keywords for this news article include: Saveh University of Medical Sciences, Algorithms, Mental Disorders, Health and Medicine, Mental Health Diseases and Conditions. [Extracted from the article]

Algorithms, Deep Learning, Life Sciences, Machine Learning, Mathematical Biosciences and Engineering, Technology Keywords: Algorithms; Deep Learning; Life Sciences; Machine Learning; Mathematical Biosciences and Engineering; Technology EN Algorithms Deep Learning Life Sciences Machine Learning Mathematical Biosciences and Engineering Technology 50 50 1 05/22/23 20230526 NES 230526 2023 MAY 27 (NewsRx) -- By a News Reporter-Staff News Editor at Medical Imaging Week -- New research on mathematical biosciences and engineering is the subject of a new report. [Extracted from the article]

Keywords: Nanjing; People's Republic of China; Asia; Diabetes Research; Algorithms; Diagnostics and Screening; Health and Medicine; Networks; Neural Networks EN Nanjing People's Republic of China Asia Diabetes Research Algorithms Diagnostics and Screening Health and Medicine Networks Neural Networks 55 55 1 05/02/23 20230501 NES 230501 2023 MAY 1 (NewsRx) -- By a News Reporter-Staff News Editor at Diabetes Week -- Investigators publish new report on Diabetes Research. We proposed a novel data pre-processing method that translates the collected metabolite data into corresponding images followed by a normalization function, which is efficient for the deep neural network to extract robust features from metabolite data and mining the potential biomarkers of diseases. [Extracted from the article]

Keywords: Algorithms; COVID-19; Coronavirus; Deep Learning; Machine Learning; RNA Viruses; Risk and Prevention; SARS-CoV-2; Severe Acute Respiratory Syndrome Coronavirus 2; Viral; Virology EN Algorithms COVID-19 Coronavirus Deep Learning Machine Learning RNA Viruses Risk and Prevention SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus 2 Viral Virology 10 10 1 04/17/23 20230421 NES 230421 2023 APR 22 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx COVID-19 Weekly -- Fresh data on COVID-19 are presented in a new report. Algorithms, COVID-19, Coronavirus, Deep Learning, Machine Learning, RNA Viruses, Risk and Prevention, SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2, Viral, Virology. [Extracted from the article]

Recurrent neural network (RNN) and long short-term memory (LSTM) models outperform the other deep learning models and vector autoregressive (VAR) model in forecasting the bilateral exchange rate movement during the COVID-19 pandemic period." Wuhan College Researchers Publish New Studies and Findings in the Area of COVID-19 (How Have the COVID-19 Pandemic and Market Sentiment Affected the FX Market? Keywords: Algorithms; COVID-19; COVID-19 Model; Coronavirus; Deep Learning; Disease Model; Epidemiology; Health and Medicine; Machine Learning; Pandemic; RNA Viruses; Risk and Prevention; SARS-CoV-2; Severe Acute Respiratory Syndrome Coronavirus 2; Viral; Virology EN Algorithms COVID-19 COVID-19 Model Coronavirus Deep Learning Disease Model Epidemiology Health and Medicine Machine Learning Pandemic RNA Viruses Risk and Prevention SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus 2 Viral Virology 1005 1005 1 04/03/23 20230409 NES 230409 2023 APR 9 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx COVID-19 Weekly -- Fresh data on COVID-19 are presented in a new report. [Extracted from the article]

According to news originating from Coimbatore, India, by NewsRx correspondents, research stated, "Autism Spectrum Disorder (ASD) is a complicated neurodevelopment disorder that is becoming more common day by day around the world. Keywords: Algorithms; Autism; Autism Spectrum Disorders; Developmental Disabilities; Developmental Diseases and Conditions; Health and Medicine; Mental Health; Neurology EN Algorithms Autism Autism Spectrum Disorders Developmental Disabilities Developmental Diseases and Conditions Health and Medicine Mental Health Neurology 2023 MAR 13 (NewsRx) -- By a News Reporter-Staff News Editor at Mental Health Weekly Digest -- New study results on autism spectrum disorders have been published. [Extracted from the article]

Acupuncture Therapy, Algorithms, Complementary and Alternative Medicine, Diagnostics and Screening, Electric Stimulation Therapy, Electroacupuncture, Electroencephalography, Health and Medicine, Networks, Neural Networks Keywords: Acupuncture Therapy; Algorithms; Complementary and Alternative Medicine; Diagnostics and Screening; Electric Stimulation Therapy; Electroacupuncture; Electroencephalography; Health and Medicine; Networks; Neural Networks EN Acupuncture Therapy Algorithms Complementary and Alternative Medicine Diagnostics and Screening Electric Stimulation Therapy Electroacupuncture Electroencephalography Health and Medicine Networks Neural Networks 7156 7156 1 03/23/23 20230310 NES 230310 2023 MAR 10 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Week -- Investigators publish new report on acupuncture therapy. [Extracted from the article]

Machine learning and blockchain are two distinct technical fields: machine learning deals with data analysis and prediction, whereas blockchain emphasizes maintaining data security. Keywords: Algorithms; Blockchain Technology; Cyborgs; Diabetic Angiopathies; Diabetic Retinopathy; Emerging Technologies; Eye Diseases and Conditions; Health and Medicine; Machine Learning; Nutritional and Metabolic Diseases and Conditions; Ophthalmology; Retinal Diseases and Conditions; Retinopathy; Technology; Vascular Diseases and Conditions EN Algorithms Blockchain Technology Cyborgs Diabetic Angiopathies Diabetic Retinopathy Emerging Technologies Eye Diseases and Conditions Health and Medicine Machine Learning Nutritional and Metabolic Diseases and Conditions Ophthalmology Retinal Diseases and Conditions Retinopathy Technology Vascular Diseases and Conditions 2023 FEB 20 (NewsRx) -- By a News Reporter-Staff News Editor at Diabetes Week -- Researchers detail new data in blockchain technology. [Extracted from the article]