Academic Articles & Research Papers

DATA MINING AND MACHINE LEARNING IN ASTRONOMY

We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding ...

Pattern Recognition and Machine Learning

Machine Learning Techniques for Multimedia

Toward disease-associated fecal microbiome signatures for domestic mammals.

Optimizing brain functional-structural architecture with cTBS to reduce relapse in alcohol use disorder: a randomized controlled trial.

Improving Parameter Recovery in Computational Models: Employing Outlier-Insensitive Loss Functions.

Brain network-based stratification of mental health disorders: design and cohort description of the STRATIFY and ESTRA studies.

Guiding functional near-infrared spectroscopy research on sedentary behavior and brain health.

Gut Microbiome in Depression with and without REM Sleep Behavior Disorder.

Subtyping psychotic disorders using a data-driven approach reveals divergent cortical and cellular signatures.

New 3H-1,2-Dithiole-3-thione derivatives: Design and synthesis, H(2)S-release profile, in vitro anticancer activity, and in silico multi-target assessment.

Quantum-classical hybrid information processing via a single quantum system

Current quantum technologies bring a new integration of quantum data with classical data for hybrid processing. However, the frameworks of these technologies are restricted to a single classical or quantum task, which limits their flexibili...

Using machine learning to predict persecutory beliefs based on aetiological models of delusions identified in a systematic literature search

Abstract Aetiological models of delusions propose a broad range of predictors. The extent to which these predictors explain variance in persecutory beliefs across the continuum requires systematic investigation. As part of a previous review...

A State-of-the-Art Review on Machine Learning-based Methods for Prostate Cancer Diagnosis

Prostate cancer can be viewed as the second most dangerous and diagnosed cancer of men all over the world. In the past decade, machine and deep learning methods play a significant role in improving the accuracy of classification for both bi...

Decentralized Distributed Sequential Neural Networks Inference on Low-Power Microcontrollers in Wireless Sensor Networks: A Predictive Maintenance Case Study

The growing adoption of IoT applications has led to increased use of low-power microcontroller units (MCUs) for energy-efficient, local data processing. However, deploying deep neural networks (DNNs) on these constrained devices is challeng...

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

BackgroundSentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its...

Hybrid-Timescale Physics-Informed Neural Network for Electrical Equivalent Impedance Identification in Induction Heating Systems

This article introduces a hybrid variant of a physics-informed neural network (PINN) that is designed to effectively capture both the rapid dynamics of electrical variables and the slower dynamics of state parameters in a domestic induction...

Fusing talent horizons: the transformative role of data integration in modern talent management

Abstract This study elucidates the transformative influence of data integration on talent management in the context of evolving technological paradigms, with a specific focus on sustainable practices in human resources. Historically anchore...

Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment

Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucid...

Application of Machine Learning for Predicting Progression‐Free and Overall Survival in Patients With Renal Cell Carcinoma

ABSTRACT Patient outcomes in advanced renal cell carcinoma (RCC) remain poor, with five‐year survival rates ranging from ~10% to 30%. Early projections of therapeutic outcomes could optimize precision medicine and accelerate drug developmen...