AIMC Topic: Machine Learning

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3D printed PEDOT:PSS-based conducting and patternable eutectogel electrodes for machine learning on textiles.

Biomaterials
The proliferation of medical wearables necessitates the development of novel electrodes for cutaneous electrophysiology. In this work, poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is combined with a deep eutectic solvent (DES) a...

Enhancing wrist arthroscopy: artificial intelligence applications for bone structure recognition using machine learning.

Hand surgery & rehabilitation
INTRODUCTION: Wrist arthroscopy is a rapidly expanding surgical discipline, but has a long and challenging learning curve. One of its difficulties is distinguishing the various anatomical structures during the procedure. Although artificial intellige...

Machine learning prediction on wetland succession and the impact of artificial structures from a decade of field data.

The Science of the total environment
The artificial structures can influence wetland topology and sediment properties, thereby shaping plant distribution and composition. Macrobenthos composition was correlated with plant cover. Previous studies on the impact of artificial structures on...

Predicting kidney allograft survival with explainable machine learning.

Transplant immunology
INTRODUCTION: Despite significant progress over the last decades in the survival of kidney allografts, several risk factors remain contributing to worsening kidney function or even loss of transplants. We aimed to evaluate a new machine learning meth...

Impact of quantum and neuromorphic computing on biomolecular simulations: Current status and perspectives.

Current opinion in structural biology
New high-performance computing architectures are becoming operative, in addition to exascale computers. Quantum computers (QC) solve optimization problems with unprecedented efficiency and speed, while neuromorphic hardware (NMH) simulates neural net...

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

Journal of neuro-oncology
PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this...

Predicting the Predicted: A Comparison of Machine Learning-Based Collision Cross-Section Prediction Models for Small Molecules.

Analytical chemistry
The application of machine learning (ML) to -omics research is growing at an exponential rate owing to the increasing availability of large amounts of data for model training. Specifically, in metabolomics, ML has enabled the prediction of tandem mas...

Investigation of the usefulness of a bile duct biopsy and bile cytology using a hyperspectral camera and machine learning.

Pathology international
To improve the efficiency of pathological diagnoses, the development of automatic pathological diagnostic systems using artificial intelligence (AI) is progressing; however, problems include the low interpretability of AI technology and the need for ...

Early diagnosis of persons with von Willebrand disease using a machine learning algorithm and real-world data.

Expert review of hematology
BACKGROUND: Von Willebrand disease (VWD) is underdiagnosed, often delaying treatment. VWD claims coding is limited and includes no severity qualifiers; improved identification methods for VWD are needed. The aim of this study is to identify and chara...