Dear Editor,This letter deals with the tracking problem for non-cooperative maneuvering targets based on the underwater sensor networks. Considering the acoustic intensity feature of underwater targets, a feature-aide...Dear Editor,This letter deals with the tracking problem for non-cooperative maneuvering targets based on the underwater sensor networks. Considering the acoustic intensity feature of underwater targets, a feature-aided multi-model tracking method for maneuvering targets is proposed.展开更多
Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease(AD).Most studies predominantly employ Convolutional Neural Networks(CNNs),which focus solely on l...Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease(AD).Most studies predominantly employ Convolutional Neural Networks(CNNs),which focus solely on local features,thus encountering difficulties in handling global features.In contrast to natural images,Structural Magnetic Resonance Imaging(sMRI)images exhibit a higher number of channel dimensions.However,during the Position Embedding stage ofMulti Head Self Attention(MHSA),the coded information related to the channel dimension is disregarded.To tackle these issues,we propose theRepBoTNet-CESA network,an advanced AD-aided diagnostic model that is capable of learning local and global features simultaneously.It combines the advantages of CNN networks in capturing local information and Transformer networks in integrating global information,reducing computational costs while achieving excellent classification performance.Moreover,it uses the Cubic Embedding Self Attention(CESA)proposed in this paper to incorporate the channel code information,enhancing the classification performance within the Transformer structure.Finally,the RepBoTNet-CESA performs well in various AD-aided diagnosis tasks,with an accuracy of 96.58%,precision of 97.26%,and recall of 96.23%in the AD/NC task;an accuracy of 92.75%,precision of 92.84%,and recall of 93.18%in the EMCI/NC task;and an accuracy of 80.97%,precision of 83.86%,and recall of 80.91%in the AD/EMCI/LMCI/NC task.This demonstrates that RepBoTNet-CESA delivers outstanding outcomes in various AD-aided diagnostic tasks.Furthermore,our study has shown that MHSA exhibits superior performance compared to conventional attention mechanisms in enhancing ResNet performance.Besides,the Deeper RepBoTNet-CESA network fails to make further progress in AD-aided diagnostic tasks.展开更多
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
目的研究正在高效联合抗反转录病毒治疗(highly active antiretroviral therapy,HAART)治疗AIDS患者因不同因素引起的股骨颈骨折人工髋关节置换手术治疗效果及并发症分析,为AIDS患者股骨颈骨折手术治疗的术前评估、手术治疗效果及并发...目的研究正在高效联合抗反转录病毒治疗(highly active antiretroviral therapy,HAART)治疗AIDS患者因不同因素引起的股骨颈骨折人工髋关节置换手术治疗效果及并发症分析,为AIDS患者股骨颈骨折手术治疗的术前评估、手术治疗效果及并发症的预防提供可靠的参考依据。方法分析2015年6月—2019年6月期间河南省传染病医院收治的正在HAART治疗152例因不同因素(摔倒跌伤、交通事故伤、高处坠落伤、非暴力伤)引起的股骨颈骨折AIDS患者,进行人工全髋关节置换术治疗,观察术后关节活动功能及并发症发生情况,回顾性分析所有患者的随访资料。结果入组AIDS患者共152例,均采取围手术期规范化处理,均采取标准的人工全髋关节置换术。术后随访平均12个月,术后离床活动时间平均为(2±1.5)天,优良率97.4%。无关节假体松动及断裂出现,未发现症状性静脉血栓发生,97例患者出现围手术期血红蛋白(Hb)与出血量、输血量等预算明显不一致,称之为不对称性贫血,21例出现低蛋白血症及电解质紊乱,出现3例血培养均为大肠埃希氏菌菌血症,3例出现肺部感染(1例为流感嗜血杆菌、2例为肺炎克雷伯杆菌),而无切口感染,依据临床经验和药物敏感性试验,给予敏感抗菌药物抗感染治疗,均得到完全治愈,所有患者术后疼痛迅速消失,关节功能迅速恢复,均恢复正常的日常生活及工作。结论AIDS患者股骨颈骨折人工全髋关节置换手术治疗取得满意的疗效,安全有效,重视和加强AIDS患者骨科围手术期处理,积极采取有效措施,使患者机体内环境接近正常状态,降低围手术期严重并发症,才能保障AIDS患者围手术期安全。展开更多
基金supported by the National Natural Science Foundation of China (62173299, U1909206)the Zhejiang Provincial Natural Science Foundation of China (LZ23F030006)+1 种基金the Joint Fund of Ministry of Education for Pre-research of Equipment (8091B022147)the Fundamental Research Funds for the Central Universities (xtr072022001)。
文摘Dear Editor,This letter deals with the tracking problem for non-cooperative maneuvering targets based on the underwater sensor networks. Considering the acoustic intensity feature of underwater targets, a feature-aided multi-model tracking method for maneuvering targets is proposed.
基金the Key Project of Zhejiang Provincial Natural Science Foundation under Grants LD21F020001,Z20F020022the National Natural Science Foundation of China under Grants 62072340,62076185the Major Project of Wenzhou Natural Science Foundation under Grants 2021HZSY0071,ZS2022001.
文摘Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease(AD).Most studies predominantly employ Convolutional Neural Networks(CNNs),which focus solely on local features,thus encountering difficulties in handling global features.In contrast to natural images,Structural Magnetic Resonance Imaging(sMRI)images exhibit a higher number of channel dimensions.However,during the Position Embedding stage ofMulti Head Self Attention(MHSA),the coded information related to the channel dimension is disregarded.To tackle these issues,we propose theRepBoTNet-CESA network,an advanced AD-aided diagnostic model that is capable of learning local and global features simultaneously.It combines the advantages of CNN networks in capturing local information and Transformer networks in integrating global information,reducing computational costs while achieving excellent classification performance.Moreover,it uses the Cubic Embedding Self Attention(CESA)proposed in this paper to incorporate the channel code information,enhancing the classification performance within the Transformer structure.Finally,the RepBoTNet-CESA performs well in various AD-aided diagnosis tasks,with an accuracy of 96.58%,precision of 97.26%,and recall of 96.23%in the AD/NC task;an accuracy of 92.75%,precision of 92.84%,and recall of 93.18%in the EMCI/NC task;and an accuracy of 80.97%,precision of 83.86%,and recall of 80.91%in the AD/EMCI/LMCI/NC task.This demonstrates that RepBoTNet-CESA delivers outstanding outcomes in various AD-aided diagnostic tasks.Furthermore,our study has shown that MHSA exhibits superior performance compared to conventional attention mechanisms in enhancing ResNet performance.Besides,the Deeper RepBoTNet-CESA network fails to make further progress in AD-aided diagnostic tasks.
文摘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.
文摘目的研究正在高效联合抗反转录病毒治疗(highly active antiretroviral therapy,HAART)治疗AIDS患者因不同因素引起的股骨颈骨折人工髋关节置换手术治疗效果及并发症分析,为AIDS患者股骨颈骨折手术治疗的术前评估、手术治疗效果及并发症的预防提供可靠的参考依据。方法分析2015年6月—2019年6月期间河南省传染病医院收治的正在HAART治疗152例因不同因素(摔倒跌伤、交通事故伤、高处坠落伤、非暴力伤)引起的股骨颈骨折AIDS患者,进行人工全髋关节置换术治疗,观察术后关节活动功能及并发症发生情况,回顾性分析所有患者的随访资料。结果入组AIDS患者共152例,均采取围手术期规范化处理,均采取标准的人工全髋关节置换术。术后随访平均12个月,术后离床活动时间平均为(2±1.5)天,优良率97.4%。无关节假体松动及断裂出现,未发现症状性静脉血栓发生,97例患者出现围手术期血红蛋白(Hb)与出血量、输血量等预算明显不一致,称之为不对称性贫血,21例出现低蛋白血症及电解质紊乱,出现3例血培养均为大肠埃希氏菌菌血症,3例出现肺部感染(1例为流感嗜血杆菌、2例为肺炎克雷伯杆菌),而无切口感染,依据临床经验和药物敏感性试验,给予敏感抗菌药物抗感染治疗,均得到完全治愈,所有患者术后疼痛迅速消失,关节功能迅速恢复,均恢复正常的日常生活及工作。结论AIDS患者股骨颈骨折人工全髋关节置换手术治疗取得满意的疗效,安全有效,重视和加强AIDS患者骨科围手术期处理,积极采取有效措施,使患者机体内环境接近正常状态,降低围手术期严重并发症,才能保障AIDS患者围手术期安全。
