Primary Care

Complexity Measures of Voice Recordings as a Discriminative Tool for Parkinson's Disease.

In this paper, we have investigated the differences in the voices of Parkinson's disease (PD) and ag...

Evaluation of platelet-rich plasma from diabetic donors shows increased platelet vascular endothelial growth factor release.

BACKGROUND: Platelet-rich plasma (PRP) contains pro-angiogenic growth factors including vascular end...

Performance characteristics of an artificial intelligence based on convolutional neural network for screening conventional Papanicolaou-stained cervical smears.

BACKGROUND: The conventional Papanicolaou-stained cervical smear is the most common screening test f...

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.

Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifi...

The greater inflammatory pathway-high clinical potential by innovative predictive, preventive, and personalized medical approach.

BACKGROUND AND LIMITATIONS: Impaired wound healing (WH) and chronic inflammation are hallmarks of no...

Artificial Intelligence: A New Tool in Operating Room Management. Role of Machine Learning Models in Operating Room Optimization.

We conducted a systematic review of literature to better understand the role of new technologies in ...

Using machine learning models to improve stroke risk level classification methods of China national stroke screening.

BACKGROUND: With the character of high incidence, high prevalence and high mortality, stroke has bro...

Highly precise risk prediction model for new-onset hypertension using artificial intelligence techniques.

Hypertension is a significant public health issue. The ability to predict the risk of developing hyp...

Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.

Few studies have addressed the predictive value of arterial stiffness determined by pulse wave veloc...

Developing algorithms to predict adult onset internalizing disorders: An ensemble learning approach.

A growing literature is utilizing machine learning methods to develop psychopathology risk algorithm...

[Artificial Intelligence for the Development of Screening Parameters in the Field of Corneal Biomechanics].

Machine learning and artificial intelligence are mostly important if data analysis by knowledge-base...

A novel computer-aided diagnosis system for the early detection of hypertension based on cerebrovascular alterations.

Hypertension is a leading cause of mortality in the USA. While simple tools such as the sphygmomanom...

Building an Otoscopic screening prototype tool using deep learning.

BACKGROUND: Otologic diseases are often difficult to diagnose accurately for primary care providers....

Point-of-care cervical cancer screening using deep learning-based microholography.

Most deaths (80%) from cervical cancer occur in regions lacking adequate screening infrastructures o...

DualWMDR: Detecting epistatic interaction with dual screening and multifactor dimensionality reduction.

Detecting epistatic interaction is a typical way of identifying the genetic susceptibility of comple...

Different spexin level in obese vs normal weight children and its relationship with obesity related risk factors.

BACKGROUND AND AIMS: Spexin (SPX) is a novel peptide recently discovered as an important regulatory ...

Machine Learning Interpretation of Extended Human Papillomavirus Genotyping by Onclarity in an Asian Cervical Cancer Screening Population.

This study aimed (i) to compare the performance of the BD Onclarity human papillomavirus (HPV) assay...

Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening.

In this study, we propose a novel anomaly detection model targeting subtle brain lesions in multipar...

Identification of repurposable drugs with beneficial effects on glucose control in type 2 diabetes using machine learning.

Despite effective medications, rates of uncontrolled glucose levels in type 2 diabetes remain high. ...

: The Impact of Obesity in Patients Undergoing Robotic Partial Nephrectomy by Rosen et al. (J Endourol 2019;33(6):431-437; DOI: 10.1089/end.2019.0018).

Electrophysiological assessment of plant status outside a Faraday cage using supervised machine learning.

Living organisms have evolved complex signaling networks to drive appropriate physiological processe...