Enhancing explainability and performance of the depression detection model on social media utilizing feature engineering and LLMs [0.03%]
利用特征工程和大型语言模型增强社交媒体抑郁检测模型的可解释性和性能
Syauki Aulia Thamrin,Arbee L P Chen
Syauki Aulia Thamrin
Depression is a mental disorder that negatively affects many people worldwide. The traditional method to help diagnose depression is through questionnaires, and better diagnoses can be obtained by consulting psychiatrists. Because the metho...
Prognostic value of stress hyperglycemia ratio in critically Ill patients with acute kidney injury: a machine learning-driven retrospective cohort analysis [0.03%]
应激高血糖比值在急性肾损伤重症患者预后价值的研究：一项基于机器学习的回顾性队列研究
Yichun Shuai,Yan Liu,Xiahong Yang et al.
Yichun Shuai et al.
Objective: Acute kidney injury (AKI) is a serious complication in critically ill patients, contributing to high morbidity and mortality. The stress hyperglycemia ratio (SHR), defined as the ratio of admission blood glucos...
RQA-based identification of emotions from electrocargiogram signals for emotion regulation in children with autism spectrum disorder [0.03%]
基于RQA的心电图信号识别自闭症儿童的情绪以进行情绪调节
S Jerritta,N Sindhu
S Jerritta
Children with Autism Spectrum Disorder (ASD) have difficulties in expressing and regulating their emotions resulting in meltdowns and outbursts that make it difficult for parents, medical practitioners and caretakers. This research aims to ...
MSER: an emotion recognition method based on multi-signal information fusion [0.03%]
基于多信号信息融合的情绪识别方法
Lanai Huang,Yong Zhang,Sen Qiu et al.
Lanai Huang et al.
Purpose: Emotion recognition usually refers to the identification of people's emotional states through facial expressions, behaviors, etc. Introducing the emotion recognition method that fuses physiological signals has be...
An augmented ECG data based classification for arrhythmia using optimal feature set [0.03%]
基于最优特征集的增强ECG数据分类在心律失常中的应用
Mohammad Shahnawaz,Nikhil Kumawat,Tinku Singh et al.
Mohammad Shahnawaz et al.
Purpose: The Electrocardiogram (ECG) is a pivotal tool for diagnosing heart conditions such as arrhythmia. Prompt detection of arrhythmias through continuous ECG monitoring is crucial to prevent life-threatening incidents...
An enhanced heart disease prediction model based on linear Diophantine fuzzy-integrated supervised machine learning [0.03%]
一种基于线性Diophantine模糊集成监督机器学习的改进型心脏病预测模型
Jeevitha Kannan,Vimala Jayakumar,Nasreen Kausar et al.
Jeevitha Kannan et al.
The medical diagnosis often dealt with uncertainty and vagueness that hindered the effectiveness of conventional ML approaches. This limitation was overcome by the integration of the LDFS with ML algorithms in this study on heart disease di...
Complex temporal network analysis based on the difference visibility graph for epilepsy with and without electrical status epilepticus during sleep (ESES) patients [0.03%]
基于差异可见图的复杂时间网络分析在伴有和不伴电 Ess 的儿童良性癫痫中应用研究
Zhipeng He,Xinxin Peng,Shishi Tang et al.
Zhipeng He et al.
Epilepsy with electrical status epilepticus during sleep (ESES) is a distinct form of epileptic encephalopathy in childhood, often associated with varying degrees of neurological dysfunction. While previous studies have reported brain funct...
LDComKG: an LLM-powered dual-enhanced framework for community-aware knowledge graph completion in traditional Chinese medicine [0.03%]
基于LLM的双增强社区感知中医知识图谱补全框架LDAPKG
Xing Zeng,Ziyan Wang,Jingxian Chai et al.
Xing Zeng et al.
Background: The intricate semantics, diverse terminology, and lack of standardization in ancient Chinese medical corpora present formidable obstacles to constructing knowledge graphs (KGs). Traditional rule-based methods ...
MedGAITS: a graph autoencoder network for modeling irregular time series data in electronic medical records [0.03%]
MedGAITS：一种图自编码网络，用于建模电子健康记录中的不规则时间序列数据
Yueying Wang,Shan Jiang,Chuyue Wang et al.
Yueying Wang et al.
Purpose: The widespread adoption of electronic medical records (EMR) has facilitated the prediction of patient prognosis and disease progression, yet inherent issues such as irregular sampling and missing values continue ...
ACD2W-InceptionNeXt: adjacent class distinguished and class distance weighted InceptionNeXt-based computer-aided mayo endoscopic scoring system for still images and video segments [0.03%]
基于InceptionNeXt的计算机辅助梅奥内镜评分系统用于Still图像和视频片段（ACD2W-InceptionNeXt：相邻类区分和分类距离加权）
Yuan-Yen Chang,Ying-Yuan Cheng,Han-Po Yang et al.
Yuan-Yen Chang et al.
Ulcerative colitis (UC) is commonly assessed using the Mayo endoscopic subscore (MES), which classifies disease severity into four ordered categories. Despite its clinical utility, MES grading is prone to considerable intra- and inter-obser...