Academic Articles & Research Papers

The voice of depression: speech features as biomarkers for major depressive disorder

Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patient...

Machine learning-based diagnostic prediction of minimal change disease: model development study

Abstract Minimal change disease (MCD) is a common cause of nephrotic syndrome. Due to its rapid progression, early detection is essential; however, definitive diagnosis requires invasive kidney biopsy. This study aims to develop non-invasiv...

A feature selection and scoring scheme for dimensionality reduction in a machine learning task

Selection of important features is very vital in machine learning tasks involving high-dimensional dataset with large features. It helps in reducing the dimensionality of a dataset and improving model performance. Most of the feature select...

Artificial intelligence in cancer target identification and drug discovery

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems ...

Integrating machine learning-based molecular design with experimental validation for the discovery of EGFR inhibitors in lung cancer.

Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET)

Objective: To decrease multiple pregnancy risk and sustain optimal pregnancy chance by choosing suitable number of embryos during transfer, this study aims to construct artificial intelligence models to predict the pregnancy outcome and mul...

Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning

Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a ...

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

Purpose: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation. Design: Retrospective multicenter study. Participants: Patients diagnos...

PERMEPSY: a multicentre, randomized, double-blind proof-of-concept trial of personalized metacognitive training for adults with psychosis — a study protocol

BackgroundWhile psychological interventions are effective at improving symptoms of psychosis, accessible, cost- and time-efficient treatments remain limited. Personalized medicine has emerged as a promising approach, tailoring interventions...

Artificial Intelligence and Big Data in Public Health

Artificial intelligence and automation are topics dominating global discussions on the future of professional employment, societal change, and economic performance. In this paper, we describe fundamental concepts underlying AI and Big Data ...

Artificial Intelligence and Machine Learning in Anesthesiology

Commercial applications of artificial intelligence and machine learning have made remarkable progress recently, particularly in areas such as image recognition, natural speech processing, language translation, textual analysis, and self-lea...

Artificial intelligence: Implications for the future of work

Artificial intelligence (AI) is a broad transdisciplinary field with roots in logic, statistics, cognitive psychology, decision theory, neuroscience, linguistics, cybernetics, and computer engineering. The modern field of AI began at a smal...

Artificial intelligence and professional roles

2017 promises to be the year that artificial intelligence (AI) moves out of film and fiction and into the workplace. While automation has become commonplace in retail and services, from the ubiquitous uptake of automatic tills to the growin...

Ensemble machine learning for predicting breast cancer recurrence and mortality using clinical and hemogram data.

Tackling visual impairment: emerging avenues in ophthalmology

Visual impairment, stemming from genetic, degenerative, and traumatic causes, affects millions globally. Recent advancements in ophthalmology present novel strategies for managing and potentially reversing these conditions. Here, we explore...

Leveraging Artificial Intelligence to Predict Posterior Malleolus Fracture Extension in Tibial Shaft Fractures

Research Type: Level 3 - Retrospective cohort study, Case-control study, Meta-analysis of Level 3 studies Introduction/Purpose: Occult posterior malleolar fractures (PMFs) are reported commonly in tibial shaft fractures. Presurgical identif...

Applications of Rough Sets in Big Data Analysis: An Overview

Big data, artificial intelligence and the Internet of things (IoT) are still very popular areas in current research and industrial applications. Processing massive amounts of data generated by the IoT and stored in distributed space is not ...

Advancing genomics and integration of multi-omics for precision oncology using quantum machine learning.

Multi-omics fusion with machine learning enables robust prediction of treatment response in ovarian cancer for precision population health.

An information theoretic limit to data amplification

In recent years generative artificial intelligence has been used to create data to support scientific analysis. For example, generative adversarial networks (GANs) have been trained using Monte Carlo simulated input and then used to generat...