AIMC Topic: Machine Learning

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AI in drug development: a multidisciplinary perspective.

Molecular diversity
The introduction of a new drug to the commercial market follows a complex and long process that typically spans over several years and entails large monetary costs due to a high attrition rate. Because of this, there is an urgent need to improve this...

MolGpka: A Web Server for Small Molecule p Prediction Using a Graph-Convolutional Neural Network.

Journal of chemical information and modeling
p is an important property in the lead optimization process since the charge state of a molecule in physiologic pH plays a critical role in its biological activity, solubility, membrane permeability, metabolism, and toxicity. Accurate and fast estima...

Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level.

Sensors (Basel, Switzerland)
Depression is a severe psychological condition that affects millions of people worldwide. As depression has received more attention in recent years, it has become imperative to develop automatic methods for detecting depression. Although numerous mac...

AIoT-Enabled Rehabilitation Recognition System-Exemplified by Hybrid Lower-Limb Exercises.

Sensors (Basel, Switzerland)
Ubiquitous health management (UHM) is vital in the aging society. The UHM services with artificial intelligence of things (AIoT) can assist home-isolated healthcare in tracking rehabilitation exercises for clinical diagnosis. This study combined a pe...

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future.

Sensors (Basel, Switzerland)
With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled. It has become critical to explore how machine learning and specifically deep learning methods can be exploited to analyse healthcare ...

An interpretable multiple-instance approach for the detection of referable diabetic retinopathy in fundus images.

Scientific reports
Diabetic retinopathy (DR) is one of the leading causes of vision loss across the world. Yet despite its wide prevalence, the majority of affected people lack access to the specialized ophthalmologists and equipment required for monitoring their condi...

Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer.

Scientific reports
Colorectal cancer (CRC) is a common cause of cancer-related deaths worldwide. The CRC mRNA gene expression dataset containing 644 CRC tumor and 51 normal samples from the cancer genome atlas (TCGA) was pre-processed to identify the significant differ...

Global soil moisture data derived through machine learning trained with in-situ measurements.

Scientific data
While soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term data...