Traditional keypads and text-based passwords are vulnerable to scams and hacks, leading to enormous levels of embezzlement and frauds apart from various other threats to data security. AI based voice authentication ho...Traditional keypads and text-based passwords are vulnerable to scams and hacks, leading to enormous levels of embezzlement and frauds apart from various other threats to data security. AI based voice authentication holds unparalleled value for data protection, security, and privacy, by providing an effective alternative to traditional password-based protection. This paper reports the findings of a limited literature review that forms the basis for further research towards enhancing the reliability and security of AI voice authentication. Based on the findings of the review of existing literature, this paper proposes that integration of the blockchain technology with the AI voice authentication can significantly enhance the data security, starting from mobile devices to the security of big agencies and banks. The key processes in implementing an AI voice authentication system are proposed as a conceptual model, to facilitate further research for implementation.展开更多
Image segmentation for 3D printing and 3D visualization has become an essential component in many fields of medical research,teaching,and clinical practice.Medical image segmentation requires sophisticated computerize...Image segmentation for 3D printing and 3D visualization has become an essential component in many fields of medical research,teaching,and clinical practice.Medical image segmentation requires sophisticated computerized quantifications and visualization tools.Recently,with the development of artificial intelligence(AI)technology,tumors or organs can be quickly and accurately detected and automatically contoured from medical images.This paper introduces a platform-independent,multi-modality image registration,segmentation,and 3D visualization program,named artificial intelligence-based medical image segmentation for 3D printing and naked eye 3D visualization(AIMIS3D).YOLOV3 algorithm was used to recognize prostate organ from T2-weighted MRI images with proper training.Prostate cancer and bladder cancer were segmented based on U-net from MRI images.CT images of osteosarcoma were loaded into the platform for the segmentation of lumbar spine,osteosarcoma,vessels,and local nerves for 3D printing.Breast displacement during each radiation therapy was quantitatively evaluated by automatically identifying the position of the 3D printed plastic breast bra.Brain vessel from multimodality MRI images was segmented by using model-based transfer learning for 3D printing and naked eye 3D visualization in AIMIS3D platform.展开更多
目的分析美国国立卫生研究院(National Institute of Health,NIH)对语音生物标记物相关项目的资助情况,为我国相关领域的研究提供参考。方法检索NIH基金资助项目查询系统中所有关于语音生物标记物的研究,时间跨段设定为建库至2024年1月...目的分析美国国立卫生研究院(National Institute of Health,NIH)对语音生物标记物相关项目的资助情况,为我国相关领域的研究提供参考。方法检索NIH基金资助项目查询系统中所有关于语音生物标记物的研究,时间跨段设定为建库至2024年1月,运用NVivo 12 Plus和Excel软件进行信息挖掘和描述性分析。结果美国语音生物标记物研究项目3年内资助数量达90项,涉及31家不同类型的机构,涵盖了医疗、生物和科技等多个领域,并聚焦于儿童到老年全年龄段人群的8个项目内容、7种疾病类型。结论语音生物标记物作为一种简单易收集的数字技术具有广阔研究前景,我国医疗行业研究者应重视语音生物标记物的价值,并以此开展多角度、全方位、跨学科的纵深研究,以推动医疗科技的创新与发展。展开更多
文摘Traditional keypads and text-based passwords are vulnerable to scams and hacks, leading to enormous levels of embezzlement and frauds apart from various other threats to data security. AI based voice authentication holds unparalleled value for data protection, security, and privacy, by providing an effective alternative to traditional password-based protection. This paper reports the findings of a limited literature review that forms the basis for further research towards enhancing the reliability and security of AI voice authentication. Based on the findings of the review of existing literature, this paper proposes that integration of the blockchain technology with the AI voice authentication can significantly enhance the data security, starting from mobile devices to the security of big agencies and banks. The key processes in implementing an AI voice authentication system are proposed as a conceptual model, to facilitate further research for implementation.
文摘Image segmentation for 3D printing and 3D visualization has become an essential component in many fields of medical research,teaching,and clinical practice.Medical image segmentation requires sophisticated computerized quantifications and visualization tools.Recently,with the development of artificial intelligence(AI)technology,tumors or organs can be quickly and accurately detected and automatically contoured from medical images.This paper introduces a platform-independent,multi-modality image registration,segmentation,and 3D visualization program,named artificial intelligence-based medical image segmentation for 3D printing and naked eye 3D visualization(AIMIS3D).YOLOV3 algorithm was used to recognize prostate organ from T2-weighted MRI images with proper training.Prostate cancer and bladder cancer were segmented based on U-net from MRI images.CT images of osteosarcoma were loaded into the platform for the segmentation of lumbar spine,osteosarcoma,vessels,and local nerves for 3D printing.Breast displacement during each radiation therapy was quantitatively evaluated by automatically identifying the position of the 3D printed plastic breast bra.Brain vessel from multimodality MRI images was segmented by using model-based transfer learning for 3D printing and naked eye 3D visualization in AIMIS3D platform.
文摘目的分析美国国立卫生研究院(National Institute of Health,NIH)对语音生物标记物相关项目的资助情况,为我国相关领域的研究提供参考。方法检索NIH基金资助项目查询系统中所有关于语音生物标记物的研究,时间跨段设定为建库至2024年1月,运用NVivo 12 Plus和Excel软件进行信息挖掘和描述性分析。结果美国语音生物标记物研究项目3年内资助数量达90项,涉及31家不同类型的机构,涵盖了医疗、生物和科技等多个领域,并聚焦于儿童到老年全年龄段人群的8个项目内容、7种疾病类型。结论语音生物标记物作为一种简单易收集的数字技术具有广阔研究前景,我国医疗行业研究者应重视语音生物标记物的价值,并以此开展多角度、全方位、跨学科的纵深研究,以推动医疗科技的创新与发展。
