Enhancing Early Breast Cancer Detection with Infrared Thermography: A Comparative Evaluation of Deep Learning and Machine Learning Models by Reem Jalloul, Chethan Hasigala Krishnappa, Victor Ikechukwu Agughasi, Ramez Alkhatib

Subjects: Get full text

Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 images by Zhaojiang Yan, Chong Fang, Kaishan Song, Xiangyu Wang, Zhidan Wen, Yingxin Shang, Hui Tao, Yunfeng Lyu

Subjects: Get full text

Spatial Downscaling of Daily Temperature Minima Using Machine Learning Methods and Application to Frost Forecasting in Two Alpine Valleys by Sudheer Bhakare, Michael Matiu, Alice Crespi, Dino Zardi

“…This study examines the performance of three machine learning models—namely, Artificial Neural Network (ANN), Random Forest (RF), and Convolutional Neural Network (CNN)—for spatial downscaling of seasonal forecasts of daily minimum temperature from 12 km to 250 m horizontal resolution. …”
Get full text

Identification of Maize Kernel Varieties Using LF-NMR Combined with Image Data: An Explainable Approach Based on Machine Learning by Chunguang Bi, Xinhua Bi, Jinjing Liu, He Chen, Mohan Wang, Helong Yu, Shaozhong Song

“…To address the need for rapid and non-destructive variety identification, this study developed a novel interpretable machine learning approach that integrates low-field nuclear magnetic resonance (LF-NMR) with morphological image features through an optimized support vector machine (SVM) framework. …”
Get full text

A hybrid machine learning model for intrusion detection in wireless sensor networks leveraging data balancing and dimensionality reduction by Md. Alamin Talukder, Majdi Khalid, Nasrin Sultana

Subjects: Get full text

Data-driven insights into pre-slaughter mortality: Machine learning for predicting high dead on arrival in meat-type ducks by Chalita Jainonthee, Phutsadee Sanwisate, Panneepa Sivapirunthep, Chanporn Chaosap, Raktham Mektrirat, Sudarat Chadsuthi, Veerasak Punyapornwithaya

Subjects: Get full text

Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

Subjects: Get full text

Correction: Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning by Jakub Horvath, Pavel Jedlicka, Marie Kratka, Zdenek Kubat, Eduard Kejnovsky, Matej Lexa

Get full text

Study on influencing factors of age-adjusted Charlson comorbidity index in patients with Alzheimer's disease based on machine learning model by Jian Ding, Jian Ding, Zheng Long, Yiming Liu, Min Wang

Subjects: Get full text

Generating high-precision farmland irrigation pattern maps using remotely sensed ecological indices and machine learning algorithms by Yuqi Liu, Yang Wang, Yanling Liao, Renkuan Liao, Jirka Šimůnek

“…To address this, we utilized the Google Earth Engine (GEE) platform, integrating environmental covariates and machine learning algorithms, to generate distribution maps of irrigation patterns (micro-irrigation and surface irrigation) at a 30-meter resolution for the Turpan-Hami Basin. …”
Get full text

Machine learning-based monitoring of land cover and reclamation plantations on coal-mined landscape using Sentinel 2 data by Mayank Pandey, Alka Mishra, Singam L. Swamy, James T. Anderson, Tarun Kumar Thakur

“…This study examines the reclamation of coal mine overburdens through reforestation, using high-resolution Sentinel 2 satellite data classified by various Machine Learning (ML) algorithms. Support Vector Machine has been identified as a more accurate and effective ML algorithm compared to Random Forest and Maximum Likelihood Classifier in delineating land use and vegetation classes, particularly forests, and in distinguishing reclamation plantations into three age classes: young (4 ± 3 years), middle-aged (10 ± 2 years), and mature (15 ± 2 years). …”
Get full text

A Comparative Analysis of Business Machine Learning in Making Effective Financial Decisions Using Structural Equation Model (SEM) by A. V. L. N. Sujith, Naila Iqbal Qureshi, Venkata Harshavardhan Reddy Dornadula, Abinash Rath, Kolla Bhanu Prakash, Sitesh Kumar Singh

“…The purpose of this research is to examine the key components of machine learning in making efficient financial decisions. …”
Get full text

Clastic facies classification using machine learning-based algorithms: A case study from Rawat Basin, Sudan by Anas Mohamed Abaker Babai, Olugbenga Ajayi Ehinola, Omer.I.M. Fadul Abul Gebbayin, Mohammed Abdalla Elsharif Ibrahim

Subjects: “…Machine learning…”
Get full text

Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images by K. Lakshmi, Sibi Amaran, G. Subbulakshmi, S. Padmini, Gyanenedra Prasad Joshi, Woong Cho

Subjects: Get full text

Development and validation of an explainable machine learning model for mortality prediction among patients with infected pancreatic necrosisResearch in context by Caihong Ning, Hui Ouyang, Jie Xiao, Di Wu, Zefang Sun, Baiqi Liu, Dingcheng Shen, Xiaoyue Hong, Chiayan Lin, Jiarong Li, Lu Chen, Shuai Zhu, Xinying Li, Fada Xia, Gengwen Huang

Subjects: Get full text

Feature engineering on climate data with machine learning to understand time-lagging effects in pasture yield predictionGitHub by Thirunavukarasu Balasubramaniam, Wathsala Anupama Mohotti, Kenneth Sabir, Richi Nayak

Subjects: Get full text

Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions by Jin-Hyun Park, Yu-Bin Shin, Dooyoung Jung, Ji-Won Hur, Seung Pil Pack, Heon-Jeong Lee, Hwamin Lee, Chul-Hyun Cho, Chul-Hyun Cho

Subjects: “…machine learning…”
Get full text

Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

Subjects: “…Machine learning…”
Get full text

Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation by Nagalakshmi R, Surbhi Bhatia Khan, Ananthoju Vijay kumar, Mahesh T R, Mohammad Alojail, Saurabh Raj Sangwan, Mo Saraee

“…This study delves into the transformative potential of Machine Learning (ML) and Natural Language Processing (NLP) within the pharmaceutical industry, spotlighting their significant impact on enhancing medical research methodologies and optimizing healthcare service delivery. …”
Get full text

Vapor pressure deficit (VPD) downscaling based on multi-source remote sensing, in-situ observation, and machine learning in China by Mi Wang, Zhuowei Hu, Xiangping Liu, Wenxing Hou

“…New hydrological insights for the region: Machine learning-based downscaling methods offer a potential solution to enhance the accuracy of VPD spatiotemporal distribution. …”
Get full text