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Aging-related markers in rat urine revealed by dynamic metabolic profiling using machine learning.

Aging
The process of aging and metabolism is intimately intertwined; thus, developing biomarkers related to metabolism is critical for delaying aging. However, few studies have identified reliable markers that reflect aging trajectories based on machine le...

Direct Comparison of the Prediction of the Unbound Brain-to-Plasma Partitioning Utilizing Machine Learning Approach and Mechanistic Neuropharmacokinetic Model.

The AAPS journal
The mechanistic neuropharmacokinetic (neuroPK) model was established to predict unbound brain-to-plasma partitioning (K) by considering in vitro efflux activities of multiple drug resistance 1 (MDR1) and breast cancer resistance protein (BCRP). Herei...

Two-step machine learning method for the rapid analysis of microvascular flow in intravital video microscopy.

Scientific reports
Microvascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcir...

Deep learning-based predictive identification of neural stem cell differentiation.

Nature communications
The differentiation of neural stem cells (NSCs) into neurons is proposed to be critical in devising potential cell-based therapeutic strategies for central nervous system (CNS) diseases, however, the determination and prediction of differentiation is...

Artificial Evolution Network: A Computational Perspective on the Expansibility of the Nervous System.

IEEE transactions on neural networks and learning systems
Neurobiologists recently found the brain can use sudden emerged channels to process information. Based on this finding, we put forward a question whether we can build a computation model that is able to integrate a sudden emerged new type of perceptu...

Automated biomarker candidate discovery in imaging mass spectrometry data through spatially localized Shapley additive explanations.

Analytica chimica acta
The search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impract...

Democratising deep learning for microscopy with ZeroCostDL4Mic.

Nature communications
Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform conventional image processing pipelines. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources ...

Neuron type classification in rat brain based on integrative convolutional and tree-based recurrent neural networks.

Scientific reports
The study of cellular complexity in the nervous system based on anatomy has shown more practical and objective advantages in morphology than other perspectives on molecular, physiological, and evolutionary aspects. However, morphology-based neuron ty...

Implementing Multilabeling, ADASYN, and ReliefF Techniques for Classification of Breast Cancer Diagnostic through Machine Learning: Efficient Computer-Aided Diagnostic System.

Journal of healthcare engineering
Multilabel recognition of morphological images and detection of cancerous areas are difficult to locate in the scenario of the image redundancy and less resolution. Cancerous tissues are incredibly tiny in various scenarios. Therefore, for automatic ...

Detection of prenatal alcohol exposure using machine learning classification of resting-state functional network connectivity data.

Alcohol (Fayetteville, N.Y.)
Fetal Alcohol Spectrum Disorder (FASD), a wide range of physical and neurobehavioral abnormalities associated with prenatal alcohol exposure (PAE), is recognized as a significant public health concern. Advancements in the diagnosis of FASD have been ...