AIMC Topic: Machine Learning

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Overcoming Site Variability in Multisite fMRI Studies: an Autoencoder Framework for Enhanced Generalizability of Machine Learning Models.

Neuroinformatics
Harmonizing multisite functional magnetic resonance imaging (fMRI) data is crucial for eliminating site-specific variability that hinders the generalizability of machine learning models. Traditional harmonization techniques, such as ComBat, depend on...

Raman Spectroscopy and Machine Learning in the Diagnosis of Breast Cancer.

Lasers in medical science
The most prevalent cancer in women worldwide, breast cancer, greatly benefits from early identification for better prognoses. But traditional diagnostic techniques, like biopsies and mammograms, can require invasive procedures and lack accuracy. The ...

Comparative evaluation of machine learning algorithms for greenhouse gas emission forecasting: a case study of Turkey (2012-2021).

Environmental monitoring and assessment
Accurate forecasting of greenhouse gas (GHG) emissions is essential for assessing climate change dynamics and developing evidence-based environmental policies. This study aims to comparatively evaluate the prediction performance of various machine le...

BamClassifier: a machine learning method for assessing iron deficiency.

Scientific reports
Iron deficiency (ID) is a well-known cause of anaemia and could lead to adverse clinical and functional impairments. However, ID is under-diagnosed due to non-specific symptoms, difficulties in interpreting ambiguous assessment outcomes and suboptima...

Research of text paraphrase generation based on self-contrastive learning.

PloS one
The goal of this study is to improve the quality and diversity of text paraphrase generation, a critical task in Natural Language Generation (NLG) that requires producing semantically equivalent sentences with varied structures and expressions. Exist...

Digital soil mapping in support of voluntary carbon market programs in agricultural land.

PloS one
Voluntary carbon market (VCM) programs in agriculture depend on accurate measurements of soil organic carbon (SOC) that can be deployed at scale efficiently, but barriers are preventing widespread adoption. To overcome these challenges, we developed ...

Visual processing oscillates differently through time for adults with ADHD.

PloS one
ADHD is a neurodevelopmental disorder affecting 3-4% of Canadian adults and 2.6% of adults worldwide. Its symptoms include inattention, hyperactivity and impulsivity. Though ADHD is known to affect several brain functions and cognitive processes, lit...

A machine learning approach for detecting WPA3 downgrade attacks in next-generation Wi-Fi systems.

PloS one
This paper presents a hybrid adaptive approach based on machine learning (ML) for classifying incoming traffic, feature selection and thresholding, aimed at enhancing downgrade attack detection in Wi-Fi Protected Access 3 (WPA3) networks. The fast pr...

Predicting 30-day hospital readmissions using ClinicalT5 with structured and unstructured electronic health records.

PloS one
Hospital readmission prediction is a crucial area of research due to its impact on healthcare expenditure, patient care quality, and policy formulation. Accurate prediction of patient readmissions within 30 days post-discharge remains a considerable ...

An integrated genetic algorithm-machine learning approach for morphological optimization of high-rise residential districts in Yulin.

PloS one
The pursuit of global carbon neutrality necessitates addressing the dual challenge of enhancing solar energy utilization while improving thermal comfort in high-rise residential areas, particularly in Yulin, northern Shaanxi, China, where abundant so...