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EDST: a decision stump based ensemble algorithm for synergistic drug combination prediction
IntroductionThere are countless possibilities for drug combinations, which makes it expensive and time-consuming to rely solely on clinical trials to...
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Improved weed segmentation in UAV imagery of sorghum fields with a combined deblurring segmentation model
BackgroundEfficient and site-specific weed management is a critical step in many agricultural tasks. Image captures from drones and modern machine...
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A Machine Learning Approach to Predict MRI Brain Abnormalities in Preterm Infants Using Clinical Data
Preterm infants are prone to several neurodevelopmental impairments (NDI). Early and accurate diagnosis could cooperate in the treatment of their...
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Prediction of HIV-1 protease cleavage site from octapeptide sequence information using selected classifiers and hybrid descriptors
BackgroundIn most parts of the world, especially in underdeveloped countries, acquired immunodeficiency syndrome (AIDS) still remains a major cause...
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Reactive Oxygen Species (ROS) and ROS Scavengers in Plant Abiotic Stress Response
The surroundings in which plants live experience fluctuations in every moment. Highly dynamic processes in the cells in response to these changes in...
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Diagnosis and treatment of cystic fibrosis in India: What is at stake for develo** countries?
Cystic fibrosis (CF) is a life-threatening monogenic disease affecting thousands of people worldwide. Cystic fibrosis transmembrane conductance...
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A comparative analysis of deep learning methods for weed classification of high-resolution UAV images
Because weeds compete directly with crops for moisture, nutrients, space, and sunlight, their monitoring and control is an essential necessity in...
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Multiple instance neural networks based on sparse attention for cancer detection using T-cell receptor sequences
Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer...
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Machine learning approaches to identify systemic lupus erythematosus in anti-nuclear antibody-positive patients using genomic data and electronic health records
BackgroundAlthough the 2019 EULAR/ACR classification criteria for systemic lupus erythematosus (SLE) has required at least a positive anti-nuclear...
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SSBlazer: a genome-wide nucleotide-resolution model for predicting single-strand break sites
Single-strand breaks are the major DNA damage in the genome and serve a crucial role in various biological processes. To reveal the significance of...
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Unraveling the role of nanoparticles in improving plant resilience under environmental stress condition
BackgroundAs the world grapples with increasing agricultural demands and unpredictable environmental stressors, there is a pressing need to improve...
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Prediction of hot spots in protein–DNA binding interfaces based on discrete wavelet transform and wavelet packet transform
BackgroundIdentification of hot spots in protein–DNA binding interfaces is extremely important for understanding the underlying mechanisms of...
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MPFNet: ECG Arrhythmias Classification Based on Multi-perspective Feature Fusion
Arrhythmia is a common cardiovascular disease that can cause sudden cardiac death. The electrocardiogram (ECG) signal is often used to diagnose the...
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Unraveling Brain Synchronisation Dynamics by Explainable Neural Networks using EEG Signals: Application to Dyslexia Diagnosis
AbstractThe electrical activity of the neural processes involved in cognitive functions is captured in EEG signals, allowing the exploration of the...
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The alteration of intestinal mucosal α-synuclein expression and mucosal microbiota in Parkinson’s disease
AbstractParkinson’s disease (PD) is the second most common neurodegenerative disease but still lacks a preclinical strategy to identify it. The...
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Transcriptomic analysis of stem cells from chorionic villi uncovers the impact of chromosomes 2, 6 and 22 in the clinical manifestations of Down syndrome
BackgroundDown syndrome (DS) clinical multisystem condition is generally considered the result of a genetic imbalance generated by the extra copy of...
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Cytotoxicity and Antioxidant Activity Evaluation of Endemic Variety of the Western Ghats Garcinia gummi-gutta var papilla and Garcinia xanthochymus
Nowadays, there is a rapid increase in cancer incidence around the world. Hence, there is an urgent need for more efficient natural medicine...
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Implementation of ensemble machine learning algorithms on exome datasets for predicting early diagnosis of cancers
Classification of different cancer types is an essential step in designing a decision support model for early cancer predictions. Using various...
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Machine Learning Methods for Virus–Host Protein–Protein Interaction Prediction
The attachment of a virion to a respective cellular receptor on the host organism occurring through the virus–host protein–protein interactions...
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Application of Machine Learning Techniques in the HELIAD Study Data for the Development of Diagnostic Models in MCI and Dementia
The increase in the population’s life expectancy leads to an increase in the incidence of dementia and, therefore, in diseases such as Alzheimer’s....