期刊文献+
共找到134篇文章
< 1 2 7 >
每页显示 20 50 100
Artificial intelligence for characterization of diminutive colorectal polyps:A feasibility study comparing two computer-aided diagnosis systems
1
作者 Quirine Eunice Wennie van der Zander Ramon M Schreuder +9 位作者 Ayla Thijssen Carolus H J Kusters Nikoo Dehghani Thom Scheeve Bjorn Winkens Mirjam C M van der Ende-van Loon Peter H N de With Fons van der Sommen Ad A M Masclee Erik J Schoon 《Artificial Intelligence in Gastrointestinal Endoscopy》 2024年第1期11-22,共12页
BACKGROUND Artificial intelligence(AI)has potential in the optical diagnosis of colorectal polyps.AIM To evaluate the feasibility of the real-time use of the computer-aided diagnosis system(CADx)AI for ColoRectal Poly... BACKGROUND Artificial intelligence(AI)has potential in the optical diagnosis of colorectal polyps.AIM To evaluate the feasibility of the real-time use of the computer-aided diagnosis system(CADx)AI for ColoRectal Polyps(AI4CRP)for the optical diagnosis of diminutive colorectal polyps and to compare the performance with CAD EYE^(TM)(Fujifilm,Tokyo,Japan).CADx influence on the optical diagnosis of an expert endoscopist was also investigated.METHODS AI4CRP was developed in-house and CAD EYE was proprietary software provided by Fujifilm.Both CADxsystems exploit convolutional neural networks.Colorectal polyps were characterized as benign or premalignant and histopathology was used as gold standard.AI4CRP provided an objective assessment of its characterization by presenting a calibrated confidence characterization value(range 0.0-1.0).A predefined cut-off value of 0.6 was set with values<0.6 indicating benign and values≥0.6 indicating premalignant colorectal polyps.Low confidence characterizations were defined as values 40%around the cut-off value of 0.6(<0.36 and>0.76).Self-critical AI4CRP’s diagnostic performances excluded low confidence characterizations.RESULTS AI4CRP use was feasible and performed on 30 patients with 51 colorectal polyps.Self-critical AI4CRP,excluding 14 low confidence characterizations[27.5%(14/51)],had a diagnostic accuracy of 89.2%,sensitivity of 89.7%,and specificity of 87.5%,which was higher compared to AI4CRP.CAD EYE had a 83.7%diagnostic accuracy,74.2%sensitivity,and 100.0%specificity.Diagnostic performances of the endoscopist alone(before AI)increased nonsignificantly after reviewing the CADx characterizations of both AI4CRP and CAD EYE(AI-assisted endoscopist).Diagnostic performances of the AI-assisted endoscopist were higher compared to both CADx-systems,except for specificity for which CAD EYE performed best.CONCLUSION Real-time use of AI4CRP was feasible.Objective confidence values provided by a CADx is novel and self-critical AI4CRP showed higher diagnostic performances compared to AI4CRP. 展开更多
关键词 artificial intelligence Colorectal polyp characterization Computer aided diagnosis Diminutive colorectal polyps Optical diagnosis Self-critical artificial intelligence
下载PDF
The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine
2
作者 GAO Yuan WU Zixuan +4 位作者 SHENG Boyang ZHANG Fu CHENG Yong YAN Junfeng PENG Qinghua 《Digital Chinese Medicine》 CAS CSCD 2024年第2期101-107,共7页
Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve ... Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications. 展开更多
关键词 Traditional Chinese medicine(TCM) Eye diagnosis artificial intelligence(ai) Large-scale model Self-supervised learning Deep neural network
下载PDF
Artificial intelligence for disease diagnostics still has a long way to go
3
作者 Jian-She Yang Qiang Wang Zhong-Wei Lv 《World Journal of Radiology》 2024年第3期69-71,共3页
Artificial intelligence(AI)can sometimes resolve difficulties that other advanced technologies and humans cannot.In medical diagnostics,AI has the advantage of processing figure recognition,especially for images with ... Artificial intelligence(AI)can sometimes resolve difficulties that other advanced technologies and humans cannot.In medical diagnostics,AI has the advantage of processing figure recognition,especially for images with similar characteristics that are difficult to distinguish with the naked eye.However,the mechanisms of this advanced technique should be well-addressed to elucidate clinical issues.In this letter,regarding an original study presented by Takayama et al,we suggest that the authors should effectively illustrate the mechanism and detailed procedure that artificial intelligence techniques processing the acquired images,including the recognition of non-obvious difference between the normal parts and pathological ones,which were impossible to be distinguished by naked eyes,such as the basic constitutional elements of pixels and grayscale,special molecules or even some metal ions which involved into the diseases occurrence. 展开更多
关键词 artificial intelligence Figure recognition diagnosis ai interactive mechanisms
下载PDF
Covid-19 Diagnosis by Artificial Intelligence Based on Vibraimage Measurement of Behavioral Parameters
4
作者 Viktor Minkin Alexander Bobrov +4 位作者 Valery Akimov Еugeniia Lobanova Yana Nikolaenko Oleg Martynov George Zazulin 《Journal of Behavioral and Brain Science》 2020年第12期590-603,共14页
The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional refle... The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional reflex parameters on COVID-19, various diseases and pathologies are proposed. Micro-movements of a head for representatives of the control group (with a confirmed absence of COVID-19 disease) and a group of patients with a confirmed diagnosis of COVID-19 were studied using vibraimage technology. Parameters and criteria for the diagnosis of COVID-19 for training artificial intelligence (AI) on the control group and the patient group are proposed. 3-layer (one hidden layer) feedforward neural network (40 + 20 + 1 sigmoid neurons) was developed for AI training. AI was firstly trained on the primary sample of patients and a control group. Study of a random sample of people with trained AI was carried out and the possibility of detecting COVID-19 using the proposed method was proved a week before the onset of clinical symptoms of the disease. Number of COVID-19 diagnostic parameters was increased to 26 and AI was trained on a sample of 536 measurements, 268 patient measurement results and 268 measurement results in the control group. The achieved diagnostic accuracy was more than 99%, 4 errors per 536 measurements (2 false positive and 2 false negative), specificity 99.25% and sensitivity 99.25%. The issues of improving the accuracy and reliability of the proposed method for diagnosing COVID-19 are discussed. Further ways to improve the characteristics and applicability of the proposed method of diagnosis and self-diagnosis of COVID-19 are outlined. 展开更多
关键词 Vibraimage Health Behavior artificial Neural Networks ANN artificial intelligence ai Vestibular-Emotional Reflex diagnosis of Diseases TELEMEDICINE COVID-19
下载PDF
基于AI-SONIC^(TM) Thyroid 5.3.3.0的超声图像分析对甲状腺结节恶性风险的预测价值 被引量:2
5
作者 郭芳琪 刘晟 +2 位作者 徐磊 李勇刚 赵佳琦 《海军军医大学学报》 CAS CSCD 北大核心 2024年第1期29-36,共8页
目的探讨基于超声人工智能(AI)系统AI-SONIC^(TM)Thyroid 5.3.3.0的图像分析在甲状腺结节恶性风险评估中的应用价值。方法选取2019年4月至2021年1月海军军医大学(第二军医大学)第二附属医院收治的453例甲状腺结节患者,共573枚甲状腺结... 目的探讨基于超声人工智能(AI)系统AI-SONIC^(TM)Thyroid 5.3.3.0的图像分析在甲状腺结节恶性风险评估中的应用价值。方法选取2019年4月至2021年1月海军军医大学(第二军医大学)第二附属医院收治的453例甲状腺结节患者,共573枚甲状腺结节。以术后病理结果为金标准,通过χ^(2)检验和ROC曲线评估术前AI系统检查对不同性别分组、不同年龄分组及不同结节大小分组的甲状腺结节良恶性的鉴别诊断效能,并通过De Long检验比较术前AI系统检查与不同年资超声医师术前应用常规超声检查鉴别诊断甲状腺结节良恶性的效能。结果在术前检查的573枚甲状腺结节中,术后病理证实为恶性411枚(76.5%)、良性162枚(23.5%)。低年资超声医师应用常规超声检查鉴别诊断甲状腺结节良恶性的灵敏度、特异度、准确度分别为85.2%(350/411)、55.6%(90/162)、76.8%(440/573),AUC为0.721(95%CI 0.672~0.771);高年资超声医师鉴别诊断甲状腺结节良恶性的灵敏度、特异度、准确度分别为93.9%(386/411)、74.1%(120/162)、88.3%(506/573),AUC为0.865(95%CI 0.825~0.904);AI系统鉴别诊断甲状腺结节良恶性的灵敏度、特异度、准确度分别为92.5%(380/411)、69.1%(112/162)、85.9%(492/573),AUC为0.809(95%CI 0.764~0.854)。De Long检验结果显示,AI系统鉴别诊断甲状腺结节良恶性的AUC高于低年资超声医师(P=0.032),与高年资超声医师之间差异无统计学意义(P>0.05)。按不同性别、不同年龄分组,AI系统鉴别诊断甲状腺结节良恶性的准确度差异无统计学意义(P>0.05);按不同结节大小分组,结节最大直径为10~<15 mm时AI系统鉴别诊断甲状腺结节良恶性的AUC最大,为0.882(95%CI 0.723~0.916)。结论AI-SONICTMThyroid 5.3.3.0可识别甲状腺结节的良性和恶性声像特征,其诊断效能接近高年资超声医师,有望成为术前预测甲状腺结节恶性风险的实用工具。 展开更多
关键词 甲状腺结节 超声检查 人工智能 计算机辅助诊断
下载PDF
Role of artificial intelligence in the diagnosis of oesophageal neoplasia:2020 an endoscopic odyssey 被引量:1
6
作者 Mohamed Hussein Juana González-Bueno Puyal +2 位作者 Peter Mountney Laurence B Lovat Rehan Haidry 《World Journal of Gastroenterology》 SCIE CAS 2020年第38期5784-5796,共13页
The past decade has seen significant advances in endoscopic imaging and optical enhancements to aid early diagnosis.There is still a treatment gap due to the underdiagnosis of lesions of the oesophagus.Computer aided ... The past decade has seen significant advances in endoscopic imaging and optical enhancements to aid early diagnosis.There is still a treatment gap due to the underdiagnosis of lesions of the oesophagus.Computer aided diagnosis may play an important role in the coming years in providing an adjunct to endoscopists in the early detection and diagnosis of early oesophageal cancers,therefore curative endoscopic therapy can be offered.Research in this area of artificial intelligence is expanding and the future looks promising.In this review article we will review current advances in artificial intelligence in the oesophagus and future directions for development. 展开更多
关键词 artificial intelligence Oesophageal neoplasia Barrett's oesophagus Squamous dysplasia Computer aided diagnosis Deep learning
下载PDF
Artificial intelligence in Barrett’s esophagus: A renaissance but not a reformation 被引量:1
7
作者 Karen Chang Christian S Jackson Kenneth J Vega 《Artificial Intelligence in Gastrointestinal Endoscopy》 2020年第2期28-32,共5页
Esophageal cancer remains as one of the top ten causes of cancer-related death in the United States.The primary risk factor for esophageal adenocarcinoma is the presence of Barrett’s esophagus(BE).Currently,identific... Esophageal cancer remains as one of the top ten causes of cancer-related death in the United States.The primary risk factor for esophageal adenocarcinoma is the presence of Barrett’s esophagus(BE).Currently,identification of early dysplasia in BE patients requires an experienced endoscopist performing a diagnostic endoscopy with random 4-quadrant biopsies taken every 1-2 cm using appropriate surveillance intervals.Currently,there is significant difficulty for endoscopists to distinguish different forms of dysplastic BE as well as early adenocarcinoma due to subtleties in mucosal texture and color.This obstacle makes taking multiple random biopsies necessary for appropriate surveillance and diagnosis.Recent advances in artificial intelligence(AI)can assist gastroenterologists in identifying areas of likely dysplasia within identified BE and perform targeted biopsies,thus decreasing procedure time,sedation time,and risk to the patient along with maximizing potential biopsy yield.Though using AI represents an exciting frontier in endoscopic medicine,recent studies are limited by selection bias,generalizability,and lack of robustness for universal use.Before AI can be reliably employed for BE in the future,these issues need to be fully addressed and tested in prospective,randomized trials.Only after that is achieved,will the benefit of AI in those with BE be fully realized. 展开更多
关键词 Barrett's esophagus artificial intelligence Machine learning Cognitive neural networks Computer aided diagnosis ENDOSCOPY
下载PDF
Artificial intelligence in gastrointestinal endoscopy:The future is almost here 被引量:18
8
作者 Muthuraman Alagappan Jeremy R Glissen Brown +1 位作者 Yuichi Mori Tyler M Berzin 《World Journal of Gastrointestinal Endoscopy》 CAS 2018年第10期239-249,共11页
Artificial intelligence(AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstr... Artificial intelligence(AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of diabetic retinopathy or the diagnosis of cutaneous malignancies. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are beginning to emerge in gastrointestinal endoscopy. The most promising of these efforts have been in computeraided detection and computer-aided diagnosis of colorectal polyps, with recent systems demonstrating high sensitivity and accuracy even when compared to expert human endoscopists. AI has also been utilized to identify gastrointestinal bleeding, to detect areas of inflammation, and even to diagnose certain gastrointestinal infections. Future work in the field should concentrate on creating seamless integration of AI systems with current endoscopy platforms and electronic medical records, developing training modules to teach clinicians how to use AI tools, and determining the best means for regulation and approval of new AI technology. 展开更多
关键词 artificial intelligence Machine learning Gastrointestinal endoscopy COMPUTER-ASSISTED decision making COMPUTER-aided detection COLONIC POLYPS COLONOSCOPY COMPUTER-aided diagnosis Colorectal ADENOCARCINOMA
下载PDF
Artificial intelligence meets traditional Chinese medicine: a bridge to opening the magic box of sphygmopalpation for pulse pattern recognition 被引量:9
9
作者 LEUNG Yeuk-Lan Alice GUAN Binghe +4 位作者 CHEN Shuang CHAN Hoyin KONG Kawai LI Wenjung SHEN Jiangang 《Digital Chinese Medicine》 2021年第1期1-8,共8页
Artificial intelligence(AI) aims to mimic human cognitive functions and execute intellectual activities like that performed by humans dealing with an uncertain environment. The rapid development of AI technology provi... Artificial intelligence(AI) aims to mimic human cognitive functions and execute intellectual activities like that performed by humans dealing with an uncertain environment. The rapid development of AI technology provides powerful tools to analyze massive amounts of data, facilitating physicians to make better clinical decisions or even replace human judgment in healthcare.Advanced AI technology also creates novel opportunities for exploring the scientific basis of traditional Chinese medicine(TCM) and developing the standardization and digitization of TCM pulse diagnostic methodology. In the present study, we review and discuss the potential application of AI technology in TCM pulse diagnosis. The major contents include the following aspects:(1) a brief introduction of the general concepts and knowledge of TCM pulse diagnosis or palpation,(2) landmark developments in AI technology and the applications of common AI deep learning algorithms in medical practice,(3) the current progress of AI technology in TCM pulse diagnosis,(4) challenges and perspectives of AI technology in TCM pulse diagnosis. In conclusion, the pairing of TCM with modern AI technology will bring novel insights into understanding the scientific principles underlying TCM pulse diagnosis and creating opportunities for the development of AI deep learning technology for the standardization and digitalization of TCM pulse diagnosis. 展开更多
关键词 artificial intelligence(ai) Traditional Chinese medicine(TCM) PALPATION Pulse pattern recognition Pulse diagnosis
下载PDF
Recent advances in computerized imaging and its vital roles in liverdisease diagnosis, preoperative planning, and interventional liversurgery: A review
10
作者 Paramate Horkaew Jirapa Chansangrat +1 位作者 Nattawut Keeratibharat Doan Cong Le 《World Journal of Gastrointestinal Surgery》 SCIE 2023年第11期2382-2397,共16页
The earliest and most accurate detection of the pathological manifestations of hepatic diseases ensures effective treatments and thus positive prognostic outcomes.In clinical settings,screening and determining the ext... The earliest and most accurate detection of the pathological manifestations of hepatic diseases ensures effective treatments and thus positive prognostic outcomes.In clinical settings,screening and determining the extent of a pathology are prominent factors in preparing remedial agents and administering approp-riate therapeutic procedures.Moreover,in a patient undergoing liver resection,a realistic preoperative simulation of the subject-specific anatomy and physiology also plays a vital part in conducting initial assessments,making surgical decisions during the procedure,and anticipating postoperative results.Conventionally,various medical imaging modalities,e.g.,computed tomography,magnetic resonance imaging,and positron emission tomography,have been employed to assist in these tasks.In fact,several standardized procedures,such as lesion detection and liver segmentation,are also incorporated into prominent commercial software packages.Thus far,most integrated software as a medical device typically involves tedious interactions from the physician,such as manual delineation and empirical adjustments,as per a given patient.With the rapid progress in digital health approaches,especially medical image analysis,a wide range of computer algorithms have been proposed to facilitate those procedures.They include pattern recognition of a liver,its periphery,and lesion,as well as pre-and postoperative simulations.Prior to clinical adoption,however,software must conform to regulatory requirements set by the governing agency,for instance,valid clinical association and analytical and clinical validation.Therefore,this paper provides a detailed account and discussion of the state-of-the-art methods for liver image analyses,visualization,and simulation in the literature.Emphasis is placed upon their concepts,algorithmic classifications,merits,limitations,clinical considerations,and future research trends. 展开更多
关键词 Computer aided diagnosis Medical image analysis Pattern recognition artificial intelligence Surgical simulation Liver surgery
下载PDF
基于人工智能技术的雨量校准故障诊断与预警辅助系统研究
11
作者 孟超 刘名 +2 位作者 张二国 樊锦涛 郭少杰 《软件》 2024年第5期165-168,共4页
基于人工智能技术的雨量校准故障诊断与预警辅助系统,通过气象观测数据“云”获取设备计量数据进行预处理,采用多种数据驱动和人工智能算法,利用深度学习及神经网络,对采集的数据进行分析,对数据样本进行训练学习,诊断设备是否存在故障... 基于人工智能技术的雨量校准故障诊断与预警辅助系统,通过气象观测数据“云”获取设备计量数据进行预处理,采用多种数据驱动和人工智能算法,利用深度学习及神经网络,对采集的数据进行分析,对数据样本进行训练学习,诊断设备是否存在故障并对设备存在的风险进行预警判断。采用神经网络分析设备故障,根据分析出的设备故障情况,系统以大数据为核心、智能算法为底层逻辑模式分析并推送解决方案,有效地提升了户外计量工作效能,对气象自动站其他高精度传感器检定、校准的多源数据分析和诊断具有较好的开拓意义。 展开更多
关键词 人工智能 雨量校准 故障诊断 预警辅助
下载PDF
利用人工智能图像识别系统诊断子宫内膜细胞病理学的有效性研究
12
作者 安静 尹盼月 +4 位作者 王斌 史桂芝 钟德星 王建六 李奇灵 《西安交通大学学报(医学版)》 CAS CSCD 北大核心 2024年第2期343-347,共5页
目的探讨基于人工智能(artificial intelligence,AI)的图像识别系统对子宫内膜细胞团块良恶性诊断的有效性。方法选取2021年8月至2023年2月西安交通大学第一附属医院和西安大兴医院的子宫内膜细胞学标本,以组织病理学为金标准,对比分析A... 目的探讨基于人工智能(artificial intelligence,AI)的图像识别系统对子宫内膜细胞团块良恶性诊断的有效性。方法选取2021年8月至2023年2月西安交通大学第一附属医院和西安大兴医院的子宫内膜细胞学标本,以组织病理学为金标准,对比分析AI图像识别系统(AI诊断)和专业病理医师人工诊断(人工诊断)子宫内膜细胞团块良恶性的灵敏度、特异度、阳性预测值、阴性预测值、准确率和诊断所需时间。结果纳入分析的126例患者中,AI诊断与组织学诊断的总体符合率为92.1%(116/126),与组织学病理结果高度一致(Kappa=0.841);人工诊断和组织学诊断的总体符合率为94.4%(119/126),与组织学病理结果高度一致(Kappa=0.889)。AI诊断与人工诊断两种方法差异无统计学意义(χ^(2)=0.568,P=0.451)。AI诊断的灵敏度、特异度、阳性预测值和阴性预测值分别为91.8%、92.3%、91.8%和92.3%。126张细胞学切片,人工诊断每张切片所需6.67 min;AI诊断每张切片所需5.00 min。结论AI图像识别系统具有较高的诊断准确性、灵敏度和特异度,与专业病理医师人工诊断水平相当,在诊断子宫内膜细胞团块良恶性方面具有应用价值。 展开更多
关键词 子宫内膜癌 人工智能(ai) 细胞学 诊断 有效性
下载PDF
人工智能技术在视网膜母细胞瘤中的应用现状
13
作者 袁路 杨卫华 陆斌 《国际眼科杂志》 CAS 2024年第5期758-761,共4页
视网膜母细胞瘤是一种常见于儿童的眼部恶性肿瘤,是威胁儿童视力和生命的主要原因之一。视网膜母细胞瘤的诊断和评估一直是临床的热点问题。在过去的几年,人工智能(AI)技术的应用在医学领域取得了显著进展,为视网膜母细胞瘤的诊断和治... 视网膜母细胞瘤是一种常见于儿童的眼部恶性肿瘤,是威胁儿童视力和生命的主要原因之一。视网膜母细胞瘤的诊断和评估一直是临床的热点问题。在过去的几年,人工智能(AI)技术的应用在医学领域取得了显著进展,为视网膜母细胞瘤的诊断和治疗提供了新的机会和挑战,如利用AI算法分析海量临床数据,可以帮助医生更准确地诊断疾病,提供个性化的治疗方案。此外,AI技术还在医学图像分析、基因组学研究等多方面发挥重要作用,可以助力新药开发、改善患者预后。本文结合近年研究情况,综述AI在视网膜母细胞瘤中的应用进展。 展开更多
关键词 人工智能 视网膜母细胞瘤 疾病诊断 医学图像分析 深度学习 辅助诊断
下载PDF
基于AI+MRI的影像诊断的样本增广与批量标注方法 被引量:10
14
作者 汪红志 赵地 +3 位作者 杨丽琴 夏天 周皛月 苗志英 《波谱学杂志》 CAS CSCD 北大核心 2018年第4期447-456,共10页
训练样本是所有领域人工智能(AI)研发的关键因素.目前,基于人工智能+磁共振成像(AI+MRI)的影像诊断存在着训练样本的有效标注数量和类型无法满足研发需求的瓶颈问题.本文利用临床MRI设备对志愿者或阳性病例进行正常或重点病灶区的定量扫... 训练样本是所有领域人工智能(AI)研发的关键因素.目前,基于人工智能+磁共振成像(AI+MRI)的影像诊断存在着训练样本的有效标注数量和类型无法满足研发需求的瓶颈问题.本文利用临床MRI设备对志愿者或阳性病例进行正常或重点病灶区的定量扫描,获取高分辨率各向同性的纵向弛豫时间(T_1)、横向弛豫时间(T_2)、质子密度(Pd)和表观扩散系数(ADC)等物理信息的多维数据矩阵,作为原始数据.开发虚拟MRI技术平台,对原始数据(相当于数字人体样本)进行虚拟扫描,实现不同序列不同参数下的多种类磁共振图像输出.选择感兴趣组织具有最好边界区分度的图像种类,经有经验的影像医生对其进行手动勾画并轨迹跟踪形成三维MASK标注矩阵,作为其他种类图像的图像勾画标注模板,从而实现低成本、高效率的MRI样本增广和批量标注.该平台以临床少量阳性病例作为输入,进行样本增广和标注,极大地减少AI对实际扫描样本的要求,降低了影像医生的精力和时间投入,极大地节省了成本,并输出了数量足够的磁共振图像,为基于AI+MRI的影像诊断研发提供低成本的训练数据解决方案. 展开更多
关键词 人工智能(ai) 磁共振成像(MRI) 样本增广 批量标注 影像辅助诊断
下载PDF
基于UTAUT模型的医生人工智能辅助诊疗系统采纳意愿研究
15
作者 张紫涵 罗晨 +1 位作者 江志斌 耿娜 《中国医院管理》 北大核心 2024年第9期79-83,共5页
目的探究医生对人工智能辅助诊疗系统(aided diagnosis and treatment system,ADTS)的采纳意愿及其影响因素,厘清ADTS推行的重要环节,进而提出优化技术、管理的建议。方法在整合型技术接受使用模型的基础上添加感知风险、认知信任、法... 目的探究医生对人工智能辅助诊疗系统(aided diagnosis and treatment system,ADTS)的采纳意愿及其影响因素,厘清ADTS推行的重要环节,进而提出优化技术、管理的建议。方法在整合型技术接受使用模型的基础上添加感知风险、认知信任、法律监管等因素设计问卷,在预调研修正后对226份正式回收问卷数据进行信度和效度分析、假设检验、结构方程模型拟合,得到医生ADTS采纳意愿关系链模型。结果绩效期望、认知信任、社会影响对医生的行为意愿产生直接正向影响,其中社会影响的作用效果最大;促成因素、法律监管等存在间接影响。研究还发现,使用过ADTS的医生在绩效期望、努力期望、学习适应性等多方面赋分较高。结论落实ADTS应用应重视培训科普、建立运维体系、完善风险责任规制,需要多方合力。 展开更多
关键词 整合型技术接受使用模型 人工智能 辅助诊疗系统 采纳意愿
下载PDF
智能建造技术在装配式建筑模式中的应用研究 被引量:1
16
作者 孟祥强 王磊 《住宅产业》 2024年第4期71-73,共3页
随着科技的不断发展,智能建造技术在装配式建筑模式中的应用越来越广泛。本文主要探讨了智能建造技术在装配式建筑中的具体应用方式和效果,包括使用先进的计算机辅助设计(CAD)系统进行建筑设计,利用物联网(IOT)技术进行建筑施工过程的监... 随着科技的不断发展,智能建造技术在装配式建筑模式中的应用越来越广泛。本文主要探讨了智能建造技术在装配式建筑中的具体应用方式和效果,包括使用先进的计算机辅助设计(CAD)系统进行建筑设计,利用物联网(IOT)技术进行建筑施工过程的监控,以及通过人工智能(AI)技术优化建筑结构以提高其耐久性和安全性等。研究结果表明,智能建造技术的应用可以显著提高装配式建筑的生产效率,降低生产成本,同时也可以有效提高建筑质量和安全性。 展开更多
关键词 智能建造技术 装配式建筑 计算机辅助设计 物联网 人工智能
下载PDF
人工智能在基层全科医生实践中的应用:基于皮肤病诊断与病程管理的视角
17
作者 刘环 朱世飞 +1 位作者 陈法余 王静华 《中国全科医学》 CAS 北大核心 2024年第31期3884-3889,共6页
背景基层全科医生在皮肤病诊断和管理方面面临挑战,凸显了对人工智能(AI)辅助系统的迫切需求。AI技术在提高诊疗效率中具有潜力,但目前针对其在基层医疗实践中的应用研究相对有限。目的探讨AI辅助系统在基层全科医生皮肤病诊断与病程管... 背景基层全科医生在皮肤病诊断和管理方面面临挑战,凸显了对人工智能(AI)辅助系统的迫切需求。AI技术在提高诊疗效率中具有潜力,但目前针对其在基层医疗实践中的应用研究相对有限。目的探讨AI辅助系统在基层全科医生皮肤病诊断与病程管理中的应用效果。方法于2022年12月—2024年3月,在杭州市社区卫生服务中心招募自愿参与研究的全科医生19名,采用随机数字表法,将其分为AI组10名、对照组9名;选取该时期两组医生接诊的皮肤病患者90例,AI组50例、对照组40例。AI组医生使用睿肤AI辅助系统进行皮肤病的诊断和病程管理,对照组医生不使用AI系统、按常规流程诊治,两组医生在接诊过程中均收集了患者的病历、实验室检查结果和皮损照片。由2名皮肤病专家远程会诊,评估两组医生的诊断准确性。分别于接诊的第1、14天对患者进行皮肤病生活质量指数(DLQI)评分,对两组患者进行满意度测评,对AI组全科医生进行睿肤AI辅助系统使用体验测评。结果AI组和对照组患者的性别、年龄、学历比较,差异无统计学意义(P>0.05);两组医生的性别、年龄、学历、职称比较,差异无统计学意义(P>0.05)。AI组全科医生的皮肤病诊断准确率高于对照组(64.0%vs 37.5%,P=0.012)。治疗14 d后,AI组、对照组患者的DLQI评分较治疗前均有改善(P<0.05),AI组改善程度优于对照组(P<0.05)。AI组患者的满意度高于对照组(P=0.024),AI组患者第14天DLQI评分与患者满意度呈正相关(r_(s)=0.471,95%CI=0.186~0.683,P=0.002),DLQI评分的改善程度与患者满意度亦呈正相关(r_(s)=0.816,95%CI=0.676~0.899,P<0.001)。问卷调查结果显示,大多数医生对AI辅助系统的使用体验持积极态度,认为其在诊断选择(70.0%)、辅助诊断(80.0%)、治疗建议(60.0%)和专业知识提供方面(90.0%)具有实际价值,90.0%的医生表示会继续使用AI辅助系统。结论在基层医疗环境中应用AI辅助系统可以提升全科医生的皮肤病诊断准确率,改善患者的生活质量和就诊满意度,且大多数医生对AI辅助系统的使用体验持积极态度。 展开更多
关键词 皮肤疾病 全科医生 人工智能 ai辅助系统 初级卫生保健 诊断 疾病管理
下载PDF
超声人工智能辅助诊断系统在最大径≤2 cm的BI-RADS 4类乳腺结节诊断中的应用价值
18
作者 陈蕊 吴墅 +2 位作者 郭佳 郭芳琪 赵佳琦 《海军军医大学学报》 CAS CSCD 北大核心 2024年第5期592-598,共7页
目的探讨超声人工智能(AI)辅助诊断系统对最大径≤2 cm的乳腺影像报告与数据系统(BI-RADS)4类乳腺结节的诊断价值。方法回顾性分析2020年5月至2022年10月于上海中医药大学附属曙光医院进行超声检查并诊断为BI-RADS 4类乳腺结节的204例... 目的探讨超声人工智能(AI)辅助诊断系统对最大径≤2 cm的乳腺影像报告与数据系统(BI-RADS)4类乳腺结节的诊断价值。方法回顾性分析2020年5月至2022年10月于上海中医药大学附属曙光医院进行超声检查并诊断为BI-RADS 4类乳腺结节的204例患者共210个最大径≤2 cm结节的二维超声图像。以术后病理结果为金标准,评价常规超声和AI系统(风险评分值阈值设为0.65、0.70)对最大径≤2 cm的BI-RADS 4类乳腺结节良恶性的诊断效能。结果210个乳腺结节中良性结节94个,恶性结节116个。高年资超声医师常规超声检查诊断乳腺结节良恶性的灵敏度为92.24%,特异度为75.53%,准确度为84.76%;AI系统(阈值0.65)诊断乳腺结节良恶性的灵敏度为92.24%,特异度为71.28%,准确度为82.86%;AI系统(阈值0.70)诊断乳腺结节良恶性的灵敏度为90.52%,特异度为79.79%,准确度为85.71%。AI系统(阈值0.70)诊断BI-RADS 4a类结节的准确度高于常规超声和AI系统(阈值0.65)(79.41%vs 77.94%、75.00%)。高年资超声医师通过常规超声对最大径≤1 cm的结节诊断准确度最高,为86.36%,AI系统(阈值0.65)及AI系统(阈值0.70)准确度分别为81.82%、84.09%。结论超声AI辅助诊断系统可辅助鉴别诊断最大径≤2 cm的BI-RADS 4类乳腺结节的良恶性。 展开更多
关键词 超声检查 人工智能 计算机辅助诊断系统 乳腺肿瘤 乳腺影像报告与数据系统
下载PDF
智能化辅助诊疗设备的研究及应用进展
19
作者 冯凯帝 蒿乐乐 +1 位作者 李岩琪 席强 《中国医学装备》 2024年第2期184-188,共5页
人工智能(AI)是引领新一轮科技革命和产业变革的战略性技术,将AI技术运用于医疗健康领域具有前瞻性、重要性和必要性。当前智能数据监测设备、智能医疗仪器、疾病辅助诊疗平台、辅助诊疗综合系统等技术研发广泛开展,相关产品也逐渐运用... 人工智能(AI)是引领新一轮科技革命和产业变革的战略性技术,将AI技术运用于医疗健康领域具有前瞻性、重要性和必要性。当前智能数据监测设备、智能医疗仪器、疾病辅助诊疗平台、辅助诊疗综合系统等技术研发广泛开展,相关产品也逐渐运用于辅助医疗预防、诊断、治疗及康复中。基于AI技术在医学领域的发展近况,总结智能辅助诊疗设备在智能化监测设备、虚拟心理诊疗平台及中医辅助诊疗仪器3个领域的应用进展,旨在为AI联动疾病诊治与健康管理,实现AI和医学学科交叉提供参考。 展开更多
关键词 人工智能(ai) 智能化应用 辅助诊疗 医疗设备
下载PDF
人工智能在内镜下结直肠肿瘤诊断中的应用
20
作者 周杰璐 林嘉希 朱锦舟 《中国医疗设备》 2024年第9期136-143,共8页
结直肠癌是全球第三大常见癌症,良好的内镜下筛查项目有望降低结直肠癌的发病率和死亡率。随着计算机技术的不断提高及大数据时代的到来,人工智能技术辅助内镜下疾病诊断的相关研究蓬勃发展。结肠镜检查中的病变检测和病变定性以及计算... 结直肠癌是全球第三大常见癌症,良好的内镜下筛查项目有望降低结直肠癌的发病率和死亡率。随着计算机技术的不断提高及大数据时代的到来,人工智能技术辅助内镜下疾病诊断的相关研究蓬勃发展。结肠镜检查中的病变检测和病变定性以及计算机辅助质量改进是人工智能在胃肠病学中的主要临床应用,到目前为止已经发表了较多研究成果。本文介绍了常用的深度学习模型架构,并针对人工智能在结直肠病变检测和诊断中应用的现有临床证据进行总结,探讨未来的发展方向。 展开更多
关键词 人工智能 结肠镜检查 腺瘤检出率 计算机辅助息肉检测 计算机辅助息肉诊断 深度学习模型
下载PDF
上一页 1 2 7 下一页 到第
使用帮助 返回顶部