AIMC Topic: Humans

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Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis.

Multiple sclerosis (Houndmills, Basingstoke, England)
Artificial intelligence (AI) is the branch of science aiming at creating algorithms able to carry out tasks that typically require human intelligence. In medicine, there has been a tremendous increase in AI applications thanks to increasingly powerfu...

Improving Anticancer Drug Selection and Prioritization via Neural Learning to Rank.

Journal of chemical information and modeling
Personalized cancer treatment requires a thorough understanding of complex interactions between drugs and cancer cell lines in varying genetic and molecular contexts. To address this, high-throughput screening has been used to generate large-scale dr...

CNSMolGen: A Bidirectional Recurrent Neural Network-Based Generative Model for De Novo Central Nervous System Drug Design.

Journal of chemical information and modeling
Central nervous system (CNS) drugs have had a significant impact on treating a wide range of neurodegenerative and psychiatric disorders. In recent years, deep learning-based generative models have shown great potential for accelerating drug discover...

Quantifying the Hardness of Bioactivity Prediction Tasks for Transfer Learning.

Journal of chemical information and modeling
Today, machine learning methods are widely employed in drug discovery. However, the chronic lack of data continues to hamper their further development, validation, and application. Several modern strategies aim to mitigate the challenges associated w...

Deep Learning Model for Cosmetic Gel Classification Based on a Short-Time Fourier Transform and Spectrogram.

ACS applied materials & interfaces
Cosmetics and topical medications, such as gels, foams, creams, and lotions, are viscoelastic substances that are applied to the skin or mucous membranes. The human perception of these materials is complex and involves multiple sensory modalities. Tr...

A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations.

Cell reports methods
Predicting cellular responses to perturbations requires interpretable insights into molecular regulatory dynamics to perform reliable cell fate control, despite the confounding non-linearity of the underlying interactions. There is a growing interest...

A Retrospective Analysis of Indoor CO Measurements Obtained with a Mobile Robot during the COVID-19 Pandemic.

Sensors (Basel, Switzerland)
This work presents a retrospective analysis of indoor CO measurements obtained with a mobile robot in an educational building after the COVID-19 lockdown (May 2021), at a time when public activities resumed with mandatory local pandemic restrictions....

Lower Limb Motion Recognition with Improved SVM Based on Surface Electromyography.

Sensors (Basel, Switzerland)
During robot-assisted rehabilitation, failure to recognize lower limb movement may efficiently limit the development of exoskeleton robots, especially for individuals with knee pathology. A major challenge encountered with surface electromyography (s...

Lumbar and Thoracic Vertebrae Segmentation in CT Scans Using a 3D Multi-Object Localization and Segmentation CNN.

Tomography (Ann Arbor, Mich.)
Radiation treatment of cancers like prostate or cervix cancer requires considering nearby bone structures like vertebrae. In this work, we present and validate a novel automated method for the 3D segmentation of individual lumbar and thoracic vertebr...

A Survey of Deep Learning Methods for Estimating the Accuracy of Protein Quaternary Structure Models.

Biomolecules
The quality prediction of quaternary structure models of a protein complex, in the absence of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for ranking predicted protein complex structures and using them approp...