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Keywords for this news article include: Hyderabad, India, Asia, Antipsychotics, Chemicals, Drugs and Therapies, Electrochemicals, Health and Medicine, Mental Health, Birla Institute of Technology and Science. Keywords: Hyderabad; India; Asia; Antipsychotics; Chemicals; Drugs and Therapies; Electrochemicals; Health and Medicine; Mental Health EN Hyderabad India Asia Antipsychotics Chemicals Drugs and Therapies Electrochemicals Health and Medicine Mental Health 584 584 1 10/03/23 20231006 NES 231006 2023 OCT 6 (NewsRx) -- By a News Reporter-Staff News Editor at Mental Health Weekly Digest -- Data detailed on Mental Health have been presented. [Extracted from the article]

A study conducted in Hyderabad, India, explores the classification of brain tumors using a Triple Memristor Hopfield Neural Network optimized with Northern Goshawk Optimization. The researchers propose a method that involves pre-processing the input images, extracting features using Synchro Extracting Chirplet Transform, and classifying the images using the Triple Memristor Hopfield Neural Network. The weight parameters of the classifier are optimized using the Northern Goshawk Optimization Algorithm. The proposed method achieves higher accuracy compared to existing methods and shows promise in automating brain tumor classification. The research has been peer-reviewed and published in Biomedical Signal Processing and Control. [Extracted from the article]

New research from the University of Hyderabad in India explores the parallel interactions between linguistic and contextual factors in bilingual individuals. The study emphasizes the need for interactionist and parallelism approaches in cognitive science, moving away from sequential stage-based models. The researchers review existing evidence from different language-speaking groups of bilinguals in India, with a focus on situational context. They argue that the parallel architecture framework can serve as a theoretical foundation for understanding bilingual language processing and its interface with external factors such as social context. This research has been peer-reviewed and provides valuable insights into the field of bilingualism. [Extracted from the article]

A recent study conducted by the School of Technology in Hyderabad, India, explores the impact of the metaverse on mental health. The researchers acknowledge that while the metaverse offers numerous benefits in gaming, entertainment, and training, it also poses risks to mental health, such as escapism and post-traumatic stress disorder (PTSD). To address these concerns, the study introduces a dataset that monitors the mental health of metaverse users, focusing on escapism and PTSD. The dataset includes user-generated content, chat logs, virtual world activities, and demographic information, which have been annotated by a team of mental health experts. This research provides valuable insights into the patterns of mental health in virtual spaces and opens opportunities for further investigation. [Extracted from the article]

A recent report from Hyderabad, India highlights the increasing concern over mortality and morbidity rates associated with poisoning incidents in the country. The research emphasizes the urgent need for a comprehensive poisoning incident reporting and monitoring system at the national level. Such a registry would not only aid in planning, resource allocation, and public health research, but also serve as a valuable tool for investigating the scientific validity of using organs salvaged from poisoning cases for transplantation. The integration of toxicology event-related data in a registry has the potential to improve the quality of healthcare in clinical toxicology scenarios in India and address the growing threat of poisoning fatalities. [Extracted from the article]

Researchers at the Indian Institute of Technology (IIT) Hyderabad have conducted a study comparing machine learning models and survival analysis models in analyzing right censored heart failure data. The study found that machine learning models outperformed survival analysis models in predicting the risk of heart disease. The researchers used techniques such as Inverse Probability of Censoring Weighting (IPCW) and IPCW Bagging to modify the machine learning models and improve their performance. The average Area Under the time-dependent ROC (AUC) value for machine learning models processed using IPCW Bagging was 0.82, indicating their effectiveness in analyzing time-to-event data. [Extracted from the article]

A recent report discusses research conducted at the University of Hyderabad in India on the use of network analysis to interpret signals in the diagnosis and detection of epilepsy. The researchers employed a simplicial approach, analyzing cliques of visibility graphs to obtain maximal cliques and evaluate network topological properties. The results showed that the proposed algorithm was effective in detecting epileptic EEG signals with high accuracy. This research has been peer-reviewed and provides a promising approach to automating the diagnosis of epilepsy. [Extracted from the article]

A research study conducted in Hyderabad, India, proposes the development of a Convolutional Neural Network (CNN) model to predict and prevent food spoilage. The researchers aim to minimize food waste and extend the shelf life of food by using innovative techniques. They have created a prototype system that uses sensors and actuators to monitor the gas emission level, humidity level, and temperature of fruits and vegetables. The model used in the study achieved a 96.3% accuracy rate. This research has implications for consumers, retailers, and food producers in reducing food waste and maintaining food quality. [Extracted from the article]

A recent study conducted by researchers at the Indian Institute of Technology (IIT) Hyderabad has proposed a new technique for the early detection of breast cancer tumors. The study introduces a hybrid semantic segmentation network that utilizes the DenseNet-121 model with an Attention-based Pyramid Scene Parsing Network (Att-PSPnet). The network incorporates features such as Adaptive Local Gamma Correction (ALGC), Attention Gate mechanism, pyramid dilated convolution module (PDM), and global average pooling (GAP) layer to enhance the accuracy of predictions. The proposed method achieved a prediction accuracy of 94.68%, surpassing existing approaches. The study has been peer-reviewed and provides valuable insights into breast cancer detection. [Extracted from the article]

A recent study conducted in Hyderabad, India, focuses on the detection of Autism Spectrum Disorder (ASD) using a Deep Quantum Neural Network (DQNN) trained by Fractional Social Driving Training-Based Optimization (FSDTBO). The study highlights the challenges of diagnosing ASD at an early stage and emphasizes the importance of communication issues, social interaction, and limited interest behaviors as key characteristics of autism in children. The research concludes that the proposed method achieved high classification performance with superior values of accuracy, specificity, and sensitivity. This study provides valuable insights into the detection and understanding of ASD. [Extracted from the article]

Keywords: Hyderabad; India; Asia; Cancer; Health and Medicine; Lung Cancer; Lung Diseases and Conditions; Lung Neoplasms; Oncology EN Hyderabad India Asia Cancer Health and Medicine Lung Cancer Lung Diseases and Conditions Lung Neoplasms Oncology 586 586 1 11/06/23 20231107 NES 231107 2023 NOV 7 (NewsRx) -- By a News Reporter-Staff News Editor at Cancer Weekly -- A new study on Oncology - Lung Cancer is now available. According to the news editors, the research concluded: "The proposed MNPS-MEFL approach improves the accuracy of lung cancer prognosis and has the potential to benefit lung disorder patients. [Extracted from the article]

Keywords: Hyderabad; India; Asia; Pain and Central Nervous System EN Hyderabad India Asia Pain and Central Nervous System 437 437 1 08/07/23 20230807 NES 230807 2023 AUG 7 (NewsRx) -- By a News Reporter-Staff News Editor at Pain & Central Nervous System Week -- Research findings on Pain and Central Nervous System are discussed in a new report. The optimal filter-bank based on the dyadic boundary points based empirical wavelet transform (DBPEWT) is introduced for the multiscale decomposition of EEG signal into various sub-band (SB) signals. The filtered EEG signal is calculated based on the linear combination of the filtered first sub-band signal evaluated from the SGDTV stage with other sub-band signals of the contaminated EEG signal. [Extracted from the article]

India, Asia, Alzheimer Disease, Brain Diseases and Conditions, Central Nervous System Diseases and Conditions, Dementia, Health and Medicine, Neurodegenerative Diseases and Conditions, Tauopathies, Hyderabad Keywords: Hyderabad; India; Asia; Alzheimer Disease; Brain Diseases and Conditions; Central Nervous System Diseases and Conditions; Dementia; Health and Medicine; Neurodegenerative Diseases and Conditions; Tauopathies EN Hyderabad India Asia Alzheimer Disease Brain Diseases and Conditions Central Nervous System Diseases and Conditions Dementia Health and Medicine Neurodegenerative Diseases and Conditions Tauopathies 716 716 1 04/17/23 20230421 NES 230421 2023 APR 17 (NewsRx) -- By a News Reporter-Staff News Editor at Pain & Central Nervous System Week -- Researchers detail new data in Neurodegenerative Diseases and Conditions - Alzheimer Disease. [Extracted from the article]

Keywords: Hyderabad; India; Asia; Cardiovascular Research EN Hyderabad India Asia Cardiovascular Research 713 713 1 04/17/23 20230417 NES 230417 2023 APR 17 (NewsRx) -- By a News Reporter-Staff News Editor at Cardiovascular Week -- Investigators publish new report on Cardiovascular Research. The news correspondents obtained a quote from the research from the Department of ECE, "The features are extracted using our new designed wavelet, i.e., Pattern adaptive wavelet and the existing symlet4 wavelet. [Extracted from the article]