An Exploratory Network Analysis of Discussion Topics About Autism Across Subreddit Communities by Skylar DeWitt, Kendall Mills, Adam M. Briggs

“…Using an inductive computational approach, our present data exploration sought to use machine learning methodology to define and identify patterns and gain insight into autism-related discussions on Reddit across three different categories of subreddits: (a) individuals who self-identify as autistic, (b) parents of individuals on the autism spectrum, and (c) behavior therapists. …”
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Unveiling the molecular mechanisms of stigmasterol on diabetic retinopathy: BNM framework construction and experimental validation by Hongrong Zhang, Yufan Li, Qi Xu, Zhaohui Fang

“…The combined use of the traditional Chinese medicines Astragalus, Fructus ligustris, and Cornus officinalis has yielded considerable therapeutic effects in clinical DR treatment.MethodsIn this study, a multimodule framework (BNM) encompassing bioinformatics, network pharmacology, and machine learning (ML) based on molecular fingerprints was innovatively developed to thoroughly investigate the molecular mechanisms of this Chinese medicine in treating DR.ResultsA total of 40 active components and 12 core targets were identified. …”
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Editorial: Current advances in anti-infective strategies by Asmaa M. Salih Almohaidi, Fikrat M. Hassan, Hussin Rothan

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Characterization of key genes and immune cell infiltration associated with endometriosis through integrating bioinformatics and experimental analyses by Ying Peng, Xiangdong She, Ying Peng

“…Discussion Three genes (APLNR, HLA-DPA1, and AP1S2) may serve as novel therapeutic targets for diagnosing and treating patients with EM.…”
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Prediction of suicide using web based voice recordings analyzed by artificial intelligence by Agnieszka Ewa Krautz, Julia Volkening, Janik Raue, Christian Otte, Simon B. Eickhoff, Eike Ahlers, Jörg Langner

“…Abstract The integration of machine learning (ML) and deep learning models in suicide risk assessment has advanced significantly in recent years. …”
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Artificial Intelligence in bone Metastases: A systematic review in guideline adherence of 92 studies by Lotte R. van der Linden, Ioannis Vavliakis, Tom M. de Groot, Paul C. Jutte, Job N. Doornberg, Santiago A. Lozano-Calderon, Olivier Q. Groot

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TCMHTI: a Transformer-based herb-target interaction prediction model for Qingfu Juanbi Decoction in rheumatoid arthritis by Zhenzhong Liang, Changsong Ding

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Predicting the outcome of psychological treatments for borderline personality disorder and posttraumatic stress disorder: a machine learning approach to predict long-term outcome o... by Jakob Blaß, Benjamin Iffland, Philipp Herzog, Tim Kaiser, Thomas Elbert, Carolin Steuwe

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Multi-Target Mechanism of Compound Qingdai Capsule for Treatment of Psoriasis: Multi-Omics Analysis and Experimental Verification by Qiao Y, Li C, Chen C, Wu P, Yang Y, Xie M, Liu N, Gu J

“…The traditional Chinese medicine, Compound Qingdai Capsule (CQC), has shown potential benefits in treating psoriasis in clinical settings. Despite its efficacy, the molecular mechanisms underpinning its therapeutic action remain unclear.Purpose: This study aimed to unravel the molecular mechanism of Compound Qingdai Capsule for psoriasis based on the psoriasis pathogenic pathway network, integrating multi-omics analysis, systems pharmacology, machine learning modeling, and animal experimentation.Methods: Psoriasis pathogenic pathway network was constructed through employing bioinformatics analysis and psoriasis-related multi-omics data mining. …”
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Subchronic effects of HgCl2 on cognitive function and central inflammation in type 2 diabetic rats: involvement of BDNF and acetylcholinesterase by Douae Benloughmari, Samir Bikri, Samir Bikri, Meriam El Aboubi, Fatima-Zahra Yassif, Youssef Aboussaleh

“…IntroductionType 2 diabetes mellitus (T2DM) is a major global health concern frequently related with chronic low-grade inflammation and a spectrum of cognitive impairments, including deficits in learning and memory. Mercury chloride (HgCl2), a widespread environmental pollutant, is recognized for its neurotoxic properties and its capacity to trigger inflammatory responses, particularly in patients with metabolic disorders such as T2DM.AimThis study aimed to evaluate the subchronic effects of HgCl2 on cognitive performance and neuroinflammation in a rat model of T2DM, with a particular focus on the roles of BDNF and acetylcholinesterase (AChE).Materials and methodsThe experimental design included four groups: control, HgCl2-treated, diabetic, and diabetic rats treated with HgCl2. …”
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Host and bacterial urine proteomics might predict treatment outcomes for immunotherapy in advanced non-small cell lung cancer patients by David Dora, Peter Revisnyei, Peter Revisnyei, Alija Pasic, Gabriella Galffy, Edit Dulka, Anna Mihucz, Brigitta Roskó, Sara Szincsak, Anton Iliuk, Glen J. Weiss, Zoltan Lohinai, Zoltan Lohinai

“…Internal validation was performed using the Random Forest (RF) machine learning (ML) algorithm. RF was validated with a non-linear Bayesian ML model. …”
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Detection of Hepatitis C Virus Infection from Patient Sera in Cell Culture Using Semi-Automated Image Analysis by Noemi Schäfer, Paul Rothhaar, Christian Heuss, Christoph Neumann-Haefelin, Robert Thimme, Julia Dietz, Christoph Sarrazin, Paul Schnitzler, Uta Merle, Sofía Pérez-del-Pulgar, Vibor Laketa, Volker Lohmann

“…RT-qPCR-based quantification of HCV infections using patient sera suffered from a high background in the daclatasvir-treated controls. We therefore established an automated image analysis pipeline based on imaging of whole wells and iterative training of a machine learning tool, using nuclear GFP localization as a readout for HCV infection. …”
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Evaluating the Efficacy of AI-Generated Inquiry-Based Lesson Plans in Science by Gülbin Kıyıcı, Nurcan Kahraman

“…The subject matter of middle school science was treated as a case and ChatGPT was asked to create lesson plans by specifying the objectives and duration of the lessons. …”
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BASICS OF APPLICABILITY OF AI LINKED TO LEGAL ASPECTS by Sidhanta KUMAR BALABANTARAY1, Anwesha MISHRA, Prajyukta SAI, Atiurr RAHMAN

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Towards Malay named entity recognition: an open-source dataset and a multi-task framework by Yingwen Fu, Nankai Lin, Zhihe Yang, Shengyi Jiang

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Deep Knowledge Tracing Integrating Temporal Causal Inference and PINN by Faming Lu, Yingran Li, Yunxia Bao

“…Next, it treats the logical model as a ’physical model’, adds a loss term, considers the confounding factors caused by students’ answer preferences, and adjusts students’ learning ability through backdoors to obtain more accurate predictions. …”
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DASFormer: self-supervised pretraining for earthquake monitoring by Qianggang Ding, Zhichao Shen, Weiqiang Zhu, Bang Liu

“…However, current approaches for earthquake monitoring like PhaseNet and PhaseNet-2 primarily rely on supervised learning, while manually labeled DAS data is quite limited and it is difficult to obtain more annotated datasets. …”
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Artificial intelligence revolutionizing anesthesia management: advances and prospects in intelligent anesthesia technology by Yannan Cao, Yixin Wang, Hang Liu, Lei Wu

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Efectiveness Duolingo And Hello Talk Apps In Increasing Students Confidence And Motivation In Speaking Skills by PUTRI YULIANTI, Hidayati Hidayati, Irwandi Irwandi, Dian Eka Mayasari, Bq Desi Milandari

“… Speaking skill is one of the important aspects in Indonesian language learning, which aims to train students to communicate effectively and efficiently. …”
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Propagating the Prior From Shallow to Deep With a Pre‐Trained Velocity‐Model Generative Transformer Network by Randy Harsuko, Shijun Cheng, Tariq Alkhalifah

“…With the dawn of machine learning, these velocity models (or, more precisely, their distribution) can be stored accurately and efficiently in a generative model. …”
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