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Neglected physical human-robot interaction may explain variable outcomes in gait neurorehabilitation research.

During gait neurorehabilitation, many factors influence the quality of gait patterns, particularly the chosen body-weight support (BWS) device. Consequently, robotic BWS devices play a key role in gait rehabilitation of people with neurological disorders. The device transparency, support force vector direction, and attachment to the harness vary widely across existing robotic BWS devices, but the ...

Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics.

Procedures and models of computerized data analysis are becoming researchers' and practitioners' thinking partners by transforming the reasoning underlying biomedicine. Complexity theory, Network analysis and Artificial Intelligence are already approaching this discipline, intending to provide support for patient's diagnosis, prognosis and treatments. At the same time, due to the sparsity, noisine...

Kefir modulates gut microbiota and reduces DMH-associated colorectal cancer via regulation of intestinal inflammation in adulthood offsprings programmed by neonatal overfeeding.

Obesity is associated with chronic inflammation, intestinal dysbiosis, and colorectal cancer risk. The anti-cancer effects of kefir are highlighted. H...

A Review of Digital Innovations for Diet Monitoring and Precision Nutrition.

This article provides an up-to-date review of technological advances in 3 key areas related to diet monitoring and precision nutrition. First, we revi...

Towards personalized nutritional treatment for malnutrition using machine learning-based screening tools.

Early identification of patients at risk of malnutrition or who are malnourished is crucial in order to start a timely and adequate nutritional therap...

Emergent antibacterial activity of -(thiazol-2-yl)benzenesulfonamides in conjunction with cell-penetrating octaarginine.

Hybrid antimicrobials that combine the effect of two or more agents represent a promising antibacterial therapeutic strategy. In this work, we have sy...

Estimating the conditional probability of developing human papilloma virus related oropharyngeal cancer by combining machine learning and inverse Bayesian modelling.

The epidemic increase in the incidence of Human Papilloma Virus (HPV) related Oropharyngeal Squamous Cell Carcinomas (OPSCCs) in several countries wor...

Computational pharmaceutics - A new paradigm of drug delivery.

In recent decades pharmaceutics and drug delivery have become increasingly critical in the pharmaceutical industry due to longer time, higher cost, an...

Prediction Models of Early Childhood Caries Based on Machine Learning Algorithms.

In this study, we developed machine learning-based prediction models for early childhood caries and compared their performances with the traditional r...

A novel method based on machine vision system and deep learning to detect fraud in turmeric powder.

Assessing the quality of food and spices is particularly important in ensuring proper human nutrition. The use of computer vision method as a non-dest...

Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study.

In this study, we aimed to propose a novel diabetes index for the risk classification based on machine learning techniques with a high accuracy for di...

Applicability of machine learning techniques in food intake assessment: A systematic review.

The evaluation of food intake is important in scientific research and clinical practice to understand the relationship between diet and health conditi...

The Role of Artificial Intelligence and Machine Learning in Clinical Cardiac Electrophysiology.

In recent years, numerous applications for artificial intelligence (AI) in cardiology have been found, due in part to large digitized data sets and th...

Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics.

Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately ...

[Artificial intelligence, radiomics and pathomics to predict response and survival of patients treated with radiations].

Artificial intelligence approaches in medicine are more and more used and are extremely promising due to the growing number of data produced and the v...

Analysis of the performance of machine learning and deep learning methods for sex estimation of infant individuals from the analysis of 2D images of the ilium.

Reducing the subjectivity of the methods used for biological profile estimation is, at present, a priority research line in forensic anthropology. To ...

Building a Cardiovascular Disease Prediction Model for Smartwatch Users Using Machine Learning: Based on the Korea National Health and Nutrition Examination Survey.

Smartwatches have the potential to support health care in everyday life by supporting self-monitoring of health conditions and personal activities. Th...

How to replace a physiotherapist: artificial intelligence and the redistribution of expertise.

The convergence of large datasets, increased computational power, and enhanced algorithm design has led to the increased success of machine learning (...

Potential for optimizing the perioperative care in robotic prostatectomy patients by adoption of enhanced recovery after surgery principles.

Several benefits have been reported after applying the principles of enhanced recovery after surgery (ERAS) into the perioperative care of patients un...

Image-based nutrient estimation for Chinese dishes using deep learning.

Food image recognition systems facilitate dietary assessment and in turn track users' dietary behaviors. However, due to the diversity of Chinese food...