Category and perceptual learning in subjects with treated Wilson's disease. by Pengjing Xu, Zhong-Lin Lu, Xiaoping Wang, Barbara Dosher, Jiangning Zhou, Daren Zhang, Yifeng Zhou

“…To explore the relationship between category and perceptual learning, we examined both category and perceptual learning in patients with treated Wilson's disease (WD), whose basal ganglia, known to be important in category learning, were damaged by the disease. …”
Get full text

Community partnership lessons learned from the You & Me: Test and Treat study by Emily M. D’Agostino, Isa Granados, Princess Abbott-Grimes, Camille Brown-Lowery, Allyn Damman, Tigidankay Fadika, Mark Ward, Mia Cooper, Jeannine Sato, Janet Kasper, Tatiana Vizcaino, Wes Gray, Allison Swart, Amanda Sparling, Claudia G. Corchado, Christoph P. Hornik

“…The You & Me: Test and Treat (YMTT) project aimed to promote COVID-19 test and treatment access using a tiered model of community engagement and a codeveloped toolkit to foster robust community-academic partnerships. …”
Get full text

Predicting fertilizer treating of maize using digital image processing and deep learning approaches by Eshete Derb Emiru, Kassie Bishaw

Get full text

Prediction of Unconfined Compressive Strength in Cement-Treated Soils: A Machine Learning Approach by Iancu-Bogdan Teodoru, Zakaria Owusu-Yeboah, Mircea Aniculăesi, Andreea Vasilica Dascălu, Florian Hörtkorn, Alessia Amelio, Irina Lungu

“…This study integrates systematic laboratory testing with advanced machine learning techniques to predict the unconfined compressive strength (UCS) of cement-treated clayey silt from northwestern Iași, Romania. …”
Get full text

Assessing Agricultural Reuse Potential of Treated Wastewater: A Hybrid Machine Learning Approach by Daniyal Durmuş Köksal, Yeşim Ahi, Mladen Todorovic

“…This study introduces a hybrid machine learning approach to predict key effluent parameters from an advanced biological wastewater treatment plant and assesses the reuse potential of treated wastewater for irrigation. …”
Get full text

Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms by Vijaykumar S. Jatti, A. Saiyathibrahim, Arvind Yadav, Murali Krishnan R., B. Jayaprakash, Sumit Kaushal, Vinaykumar S. Jatti, Ashwini V. Jatti, Savita V. Jatti, Abhinav Kumar, Soumaya Gouadria, Ebenezer Bonyah

Get full text

Transfer learning strategies for neural networks: A case study in amine gas treating units by Daniela Galatro, Manoj Machavolu, Gladys Navas

“…This work presents a framework where strategies are applied within a workflow created to enhance the accuracy and transferability of the transfer learning process. We used a case study for predicting corrosion rates in gas-treating units, employing datasets from two different amines (A and B), where the amine A dataset is large compared to the amine B dataset. …”
Get full text

Machine learning predicting acute pain and opioid dose in radiation treated oropharyngeal cancer patients by Vivian Salama, Vivian Salama, Laia Humbert-Vidan, Brandon Godinich, Brandon Godinich, Kareem A. Wahid, Kareem A. Wahid, Dina M. ElHabashy, Mohamed A. Naser, Renjie He, Abdallah S. R. Mohamed, Ariana J. Sahli, Katherine A. Hutcheson, Gary Brandon Gunn, David I. Rosenthal, Clifton D. Fuller, Amy C. Moreno

“…This study aimed to predict acute pain severity and opioid doses during RT using machine learning (ML), facilitating risk-stratification models for clinical trials.MethodsA retrospective study examined 900 OCC/OPC patients treated with RT during 2017–2023. …”
Get full text

Using Machine Learning and Nationwide Population-Based Data to Unravel Predictors of Treated Depression in Farmers by Pascal Petit, Vincent Bonneterre, Nicolas Vuillerme

Get full text

Interpretable Ensemble Learning with Lévy Flight-Enhanced Heuristic Technique for Strength Prediction of MICP-Treated Sands by Yingui Qiu, Shibin Yao, Hongning Qi, Jian Zhou, Manoj Khandelwal

“…This study develops an ensemble learning framework (LARO-EnML) for predicting the unconfined compressive strength (UCS) of MICP-treated sand. …”
Get full text

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…The simplicity of the model means that it is possible to analyse the relationship between patient characteristics and the probability of belonging to the treated group.…”
Get full text

Survival Prediction in Brain Metastasis Patients Treated with Stereotactic Radiosurgery: A Hybrid Machine Learning Approach by Tuğçe Öznacar, İpek Pınar Aral, Hatice Yağmur Zengin, Yılmaz Tezcan

“…Methods: We applied a hybrid machine learning approach to predict survival in brain metastasis patients treated with SRT, utilizing real-world data. …”
Get full text

Development and evaluation of machine learning models for individualized prediction of myopia control efficacy treated with overnight orthokeratology by Lan Zhang, Mingjun Gao, Yiru Wang, Siqi Zhang, Huailin Zhu, Qi Zhao

“…SVM demonstrated the highest predictive quality with an AUC of 0.877 in the training and 0.828 in the external validation set.ConclusionWe developed and validated several prediction models for individualized prediction of myopia control efficacy treated with overnight orthokeratology through machine learning, using easily obtained clinical and corneal topography features. …”
Get full text

Automated machine learning for predicting perioperative ischemia stroke in endovascularly treated ruptured intracranial aneurysm patients by Yuhang Peng, Ke Bi, Xiaolin Zhang, Ning Huang, Xiang Ji, Weifu Chen, Ying Ma, Yuan Cheng, Yongxiang Jiang, Jianhe Yue

“…ObjectiveThis study aims to develop and validate an automated machine learning model to predict perioperative ischemic stroke (PIS) risk in endovascularly treated patients with ruptured intracranial aneurysms (RIAs), with the goal of establishing a clinical decision-support tool.MethodsIn this retrospective cohort study, we analyzed RIA patients undergoing endovascular treatment at our neurosurgical center (December 2013–February 2024). …”
Get full text

Machine learning reveals immediate disruption in mosquito flight when exposed to Olyset nets by Yasser M. Qureshi, Vitaly Voloshin, Amy Guy, Hilary Ranson, Philip J. McCall, James A. Covington, Catherine E. Towers, David P. Towers

Subjects: “…Insecticide-treated nets…”
Get full text

Transformer‐based representation learning and multiple‐instance learning for cancer diagnosis exclusively from raw sequencing fragments of bisulfite‐treated plasma cell‐free DNA by Jilei Liu, Hongru Shen, Yichen Yang, Meng Yang, Qiang Zhang, Kexin Chen, Xiangchun Li

“…Here, we present a deep‐learning‐based approach for early cancer interception and diagnosis (DECIDIA) that can achieve accurate cancer diagnosis exclusively from bisulfite‐treated cfDNA sequencing fragments. …”
Get full text

Predicting visual acuity of treated ocular trauma based on pattern visual evoked potentials by machine learning models by Hongxia Hao, Jiemin Chen, Yifei Yan, Yifei Yan, Qi Zhang, Qi Zhang, Zhilu Zhou, Wentao Xia

“…PurposeTo develop effective machine learning models that analyze pattern visual evoked potentials (PVEPs) to predict the stabilized visual acuity (VA) of patients with treated ocular trauma.MethodsThis experiment included 260 patients (220 males, average age 42.54 years) with unilateral ocular trauma. …”
Get full text

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy by Eyachew Misganew Tegaw, Betelhem Bizuneh Asfaw

Get full text

Lessons learned from a multimodal sensor-based eHealth approach for treating pediatric obsessive-compulsive disorder by Carolin S. Klein, Carolin S. Klein, Karsten Hollmann, Karsten Hollmann, Jan Kühnhausen, Jan Kühnhausen, Annika K. Alt, Annika K. Alt, Anja Pascher, Anja Pascher, Lennart Seizer, Lennart Seizer, Jonas Primbs, Winfried Ilg, Annika Thierfelder, Björn Severitt, Helene Passon, Ursula Wörz, Heinrich Lautenbacher, Wolfgang A. Bethge, Johanna Löchner, Johanna Löchner, Martin Holderried, Walter Swoboda, Enkelejda Kasneci, Martin A. Giese, Christian Ernst, Gottfried M. Barth, Gottfried M. Barth, Annette Conzelmann, Annette Conzelmann, Annette Conzelmann, Michael Menth, Caterina Gawrilow, Caterina Gawrilow, Tobias J. Renner, Tobias J. Renner

Get full text

Utilizing Radiomics as Predictive Factor in Brain Metastasis Treated With Stereotactic Radiosurgery: Systematic Review and Radiomic Quality Assessment by Abdulrahman Umaru, Hanani Abdul Manan, Ramesh Kumar Athi Kumar, Siti Khadijah Hamsan, Noorazrul Yahya

“…ABSTRACT Radiomics and machine learning (ML) are increasingly utilized to predict treatment response by uncovering latent information in medical images. …”
Get full text