LIVIVO - Search results -

Search results

Result 1 - 10 of total 22

Search options

Article ; Online: Predictive deep learning models for cognitive risk using accessible data.

Karako, Kenji

2024 Volume 18, Issue 1, Page(s) 66–72

Abstract: The early detection of mild cognitive impairment (MCI) is crucial to preventing the progression of dementia. However, it necessitates that patients voluntarily undergo cognitive function tests, which may be too late if symptoms are only recognized once ... ...

Abstract	The early detection of mild cognitive impairment (MCI) is crucial to preventing the progression of dementia. However, it necessitates that patients voluntarily undergo cognitive function tests, which may be too late if symptoms are only recognized once they become apparent. Recent advances in deep learning have improved model performance, leading to applied research in various predictive problems. Studies attempting to estimate dementia and the risk of MCI based on readily available data are being conducted, with the hope of facilitating the early detection of MCI. The data used for these predictions vary widely, including facial imagery, voice recordings, blood tests, and inertial information during walking. Deep learning models that make predictions based on these data sources have been proposed. This article summarizes recent research efforts to predict the risk of dementia using easily accessible data. As research progresses and more accurate predictions become feasible, simple tests could be incorporated into daily life to monitor one's personal health status and to facilitate an early intervention.
MeSH term(s)	Humans ; Dementia/diagnosis ; Deep Learning ; Cognitive Dysfunction/diagnosis ; Cognitive Dysfunction/psychology ; Cognition ; Neuropsychological Tests ; Disease Progression ; Alzheimer Disease/diagnosis
Language	English
Publishing date	2024-02-20
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2543899-2
ISSN	1881-7823 ; 1881-7823
ISSN (online)	1881-7823
ISSN	1881-7823
DOI	10.5582/bst.2024.01026
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Article ; Online: Relaxation of all-case reporting of COVID-19 cases in Japan.

Karako, Kenji

Drug discoveries & therapeutics

2022

Abstract: Japan is facing the largest outbreak of COVID-19 in history in 2022. The number of new infections per day surpassed 200,000 for the first time in July and peaked in August. Japan has required the reporting of information on all infected persons, but ... ...

Abstract	Japan is facing the largest outbreak of COVID-19 in history in 2022. The number of new infections per day surpassed 200,000 for the first time in July and peaked in August. Japan has required the reporting of information on all infected persons, but maintaining this system is difficult. Starting in September 2, 2022, four prefectures have implemented a trial policy to limit the infected that must be reported in order to reduce the burden on medical personnel. The policy obliges medical facilities to report only people with a high-risk infection, but the number of the infected will continue to be counted regardless of whether they have a high-risk or low-risk infection. More prefectures are expected to adopt this policy in the future.
Language	English
Publishing date	2022-09-06
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2568828-5
ISSN	1881-784X ; 1881-784X
ISSN (online)	1881-784X
ISSN	1881-784X
DOI	10.5582/ddt.2022.01073
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: COVID-19 in Japan during 2020-2022: Characteristics, responses, and implications for the health care system.

Karako, Kenji / Song, Peipei / Chen, Yu / Karako, Takashi

Journal of global health

2022 Volume 12, Page(s) 3073

MeSH term(s)	COVID-19/epidemiology ; Delivery of Health Care ; Humans ; Japan/epidemiology ; SARS-CoV-2
Language	English
Publishing date	2022-10-14
Publishing country	Scotland
Document type	Journal Article
ZDB-ID	2741629-X
ISSN	2047-2986 ; 2047-2986
ISSN (online)	2047-2986
ISSN	2047-2986
DOI	10.7189/jogh.12.03073
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: An average of nearly 200,000 new infections per day over a six-week period: What is the impact of such a severe COVID-19 pandemic on the healthcare system in Japan?

Karako, Kenji / Song, Peipei / Chen, Yu / Karako, Takashi

Bioscience trends

2022 Volume 16, Issue 5, Page(s) 371–373

Abstract: During a six-week period from July 20 to August 31, 2022, Japan experienced its highest level of COVID-19 infection ever, with an average of nearly 200,000 new infections per day nationwide. Cases requiring inpatient care peaked at 1,993,062. Twenty- ... ...

Abstract	During a six-week period from July 20 to August 31, 2022, Japan experienced its highest level of COVID-19 infection ever, with an average of nearly 200,000 new infections per day nationwide. Cases requiring inpatient care peaked at 1,993,062. Twenty-seven prefectures (out of 47 prefectures) had an average hospital bed occupancy of 50% or higher, and bed occupancy in Kanagawa in particular reached 98% in mid-August. In Tokyo, bed occupancy by patients with severe COVID-19 reached 57% and peaked at 64% in mid-August. Although the number of new infections per day has decreased since September, hospital bed occupancy, the number of severe cases, and deaths remain high nationwide. Efforts including vaccination campaigns, domestic surveillance, and routine infection control measures based on the varied knowledge that the Japanese public already has should be thoroughly implemented to reduce the number of the infected in order to avoid an increase the number of serious cases and deaths.
MeSH term(s)	Humans ; COVID-19/epidemiology ; Pandemics/prevention & control ; Japan/epidemiology ; Bed Occupancy ; Delivery of Health Care
Language	English
Publishing date	2022-09-12
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2543899-2
ISSN	1881-7823 ; 1881-7823
ISSN (online)	1881-7823
ISSN	1881-7823
DOI	10.5582/bst.2022.01390
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Improving the sensitivity of liver tumor classification in ultrasound images via a power-law shot noise model.

Karako, Kenji / Mihara, Yuichiro / Hasegawa, Kiyoshi / Chen, Yu

Bioscience trends

2023 Volume 17, Issue 2, Page(s) 117–125

Abstract: Power laws have been observed in various fields and help us understand natural phenomena. Power laws have also been observed in ultrasound images. This study used the power spectrum of the signal identified from the reflected ultrasound signal observed ... ...

Abstract	Power laws have been observed in various fields and help us understand natural phenomena. Power laws have also been observed in ultrasound images. This study used the power spectrum of the signal identified from the reflected ultrasound signal observed in ultrasonography based on the power-law shot noise (PLSN) model. The power spectrum follows a power law, which has a scaling factor that depends on the characteristics of the tissue in the region where the ultrasound wave propagates. To distinguish between a tumor and blood vessels in the liver, we propose a classification model that includes a scaling factor based on ResNet, a deep learning model for image classification. In a task to classify 6 types of tissue - a tumor, the inferior vena cava, the descending aorta, the Gleason sheath, the hepatic vein, and small blood vessels - tumor sensitivity increased 3.8% and the F-score for a tumor improved 2% while precision was maintained. The scaling factor obtained using the PLSN model was validated for classification of liver tumors.
MeSH term(s)	Humans ; Ultrasonography ; Liver Neoplasms/diagnostic imaging
Language	English
Publishing date	2023-04-13
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2543899-2
ISSN	1881-7823 ; 1881-7823
ISSN (online)	1881-7823
ISSN	1881-7823
DOI	10.5582/bst.2023.01040
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: Recent deep learning models for dementia as point-of-care testing: Potential for early detection.

Karako, Kenji / Song, Peipei / Chen, Yu

Intractable & rare diseases research

2023 Volume 12, Issue 1, Page(s) 1–4

Abstract: Deep learning has been intensively researched over the last decade, yielding several new models for natural language processing, images, speech and time series processing that have dramatically improved performance. This wave of technological ... ...

Abstract	Deep learning has been intensively researched over the last decade, yielding several new models for natural language processing, images, speech and time series processing that have dramatically improved performance. This wave of technological developments in deep learning is also spreading to medicine. The effective use of deep learning in medicine is concentrated in diagnostic imaging-related applications, but deep learning has the potential to lead to early detection and prevention of diseases. Physical aspects of disease that went unnoticed can now be used in diagnosis with deep learning. In particular, deep learning models for the early detection of dementia have been proposed to predict cognitive function based on various information such as blood test results, speech, and the appearance of the face, where the effects of dementia can be seen. Deep learning is a useful diagnostic tool, as it has the potential to detect diseases early based on trivial aspects before clear signs of disease appear. The ability to easily make a simple diagnosis based on information such as blood test results, voice, pictures of the body, and lifestyle is a method suited to point-of-cate testing, which requires immediate testing at the desired time and place. Over the past few years, the process of predicting disease can now be visualized using deep learning, providing insights into new methods of diagnosis.
Language	English
Publishing date	2023-02-17
Publishing country	Japan
Document type	Editorial
ZDB-ID	2672570-8
ISSN	2186-361X ; 2186-3644
ISSN (online)	2186-361X
ISSN	2186-3644
DOI	10.5582/irdr.2023.01015
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: New possibilities for medical support systems utilizing artificial intelligence (AI) and data platforms.

Karako, Kenji / Song, Peipei / Chen, Yu / Tang, Wei

Bioscience trends

2023 Volume 17, Issue 3, Page(s) 186–189

Abstract: In Japan, there is a growing initiative to construct centralized databases and platforms that can aggregate and manage a vast range of medical, health, and caregiving data for research and analysis. Recent advancements in artificial intelligence (AI), ... ...

Abstract	In Japan, there is a growing initiative to construct centralized databases and platforms that can aggregate and manage a vast range of medical, health, and caregiving data for research and analysis. Recent advancements in artificial intelligence (AI), particularly in general-purpose models like the Segment Anything model and Chat GPT, promise significant progress towards utilizing such data-rich platforms effectively for healthcare. Traditionally, AI has displayed superior performance by learning specific images or languages, but now it is advancing towards creating models capable of learning universal traits from images and languages by training on extensive datasets. The challenge lies in the fact that these general-purpose models are trained on data that does not sufficiently incorporate medical information, making their direct application to healthcare difficult. However, the introduction of data platforms can potentially solve this problem. This would lead to the development of universally applicable models to process medical images and AI assistants that can support both doctors and patients. These medical AI assistants can function as a "sub-doctor" with extensive knowledge, assisting in comprehensive analysis of symptoms, early detection of rare diseases, and more. They can also serve as an intermediary between the doctor and the patient, helping to simplify consultations and enhance patient understanding of medical conditions and treatments. By bridging this gap, the AI assistant can help to reduce doctors' workload, improve the quality of healthcare, and facilitate early detection and prevention in the elderly population.
MeSH term(s)	Aged ; Humans ; Artificial Intelligence ; Delivery of Health Care ; Physicians ; Japan
Language	English
Publishing date	2023-06-26
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2543899-2
ISSN	1881-7823 ; 1881-7823
ISSN (online)	1881-7823
ISSN	1881-7823
DOI	10.5582/bst.2023.01138
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Comprehensive assessment and treatment strategies for dysphagia in the elderly population: Current status and prospects.

Hu, Xiqi / Ma, Ya-Nan / Karako, Kenji / Tang, Wei / Song, Peipei / Xia, Ying

Bioscience trends

2024

Abstract: As the population ages, the prevalence of dysphagia among older adults is a growing concern. Age-related declines in physiological function, coupled with neurological disorders and structural changes in the pharynx associated with aging, can result in ... ...

Abstract	As the population ages, the prevalence of dysphagia among older adults is a growing concern. Age-related declines in physiological function, coupled with neurological disorders and structural changes in the pharynx associated with aging, can result in weakened tongue propulsion, a prolonged reaction time of the submental muscles, delayed closure of the laryngeal vestibule, and delayed opening of the upper esophageal sphincter (UES), increasing the risk of dysphagia. Dysphagia impacts the physical health of the elderly, leading to serious complications such as dehydration, aspiration pneumonia, malnutrition, and even life-threatening conditions, and it also detrimentally affects their psychological and social well-being. There is a significant correlation between frailty, sarcopenia, and dysphagia in the elderly population. Therefore, older adults should be screened for dysphagia to identify both frailty and sarcopenia. A reasonable diagnostic approach for dysphagia involves screening, clinical assessment, and instrumental diagnosis. In terms of treatment, multidisciplinary collaboration, rehabilitation training, and the utilization of new technologies are essential. Future research will continue to concentrate on these areas to enhance the diagnosis and treatment of dysphagia, with the ultimate aim of enhancing the quality of life of the elderly population.
Language	English
Publishing date	2024-04-24
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2543899-2
ISSN	1881-7823 ; 1881-7823
ISSN (online)	1881-7823
ISSN	1881-7823
DOI	10.5582/bst.2024.01100
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: Relationship Between Cognitive Function, Oral Conditions and Systemic Metabolic Function in the Elderly.

Karako, Kenji / Chen, Yu / Oyama, Katsunori / Hu, Lizhen / Sakatani, Kaoru

Advances in experimental medicine and biology

2023 Volume 1438, Page(s) 27–31

Abstract: Systemic metabolic disorders, including lifestyle-related diseases, are known risk factors for dementia. Furthermore, oral diseases such as periodontal disease and tooth decay are also associated with systemic metabolic disorders such as lifestyle- ... ...

Abstract	Systemic metabolic disorders, including lifestyle-related diseases, are known risk factors for dementia. Furthermore, oral diseases such as periodontal disease and tooth decay are also associated with systemic metabolic disorders such as lifestyle-related diseases, and have also been reported to be indicators of risk factors for developing dementia. In this study, we investigated the relationship between cognitive function, oral conditions and systemic metabolic function in the elderly. We investigated the number of healthy teeth, the number of prosthetic teeth fitted, the number of missing prosthetic teeth, etc., in 41 elderly patients (69.7 ± 5.6 years old). Cognitive function was evaluated by the Mini Mental State Examination (MMSE). We also estimated MMSE scores for each subject using deep learning-based assessment of MMSE scores. This deep learning method enables the estimation of the MMSE score based on basic blood test data from medical examinations and reflects the systemic metabolic state including lifestyle-related diseases. The estimated MMSE score correlated negatively with age (r = -0.381), correlated positively with the number of healthy teeth (r = 0.37), and correlated negatively with the number of missing prosthetic teeth (r = -0.39). This relationship was not found in the measured MMSE scores. A negative correlation (r = -0.36) was found between age and the current number of teeth and a positive correlation (r = 0.37) was found between age and the number of missing prosthetic teeth. A positive correlation was found between the number of teeth requiring prosthesis and lifestyle-related diseases. The deep learning-based estimation method of cognitive function clearly demonstrated the close relationship between oral health condition, systemic metabolic function and the risk of cognitive impairment. It was determined that the smaller the number of existing teeth and the larger the number of missing prosthetic teeth, the higher is the risk of cognitive impairment. Systemic metabolic function is presumed to affect oral health and cognitive function. Interestingly, no such relationship was found in the measured MMSE scores. There are two possible reasons for this. The first is that MMSE is a subjective test and is less accurate in assessing cognitive function. The second is that because the MMSE estimated based on blood data using deep learning is calculated based on the metabolic function, it has a stronger correlation with the oral health condition affected by the metabolic function. In conclusion, oral health condition may predict cognitive impairment in the elderly.
MeSH term(s)	Humans ; Aged ; Middle Aged ; Cognitive Dysfunction/diagnosis ; Cognitive Dysfunction/complications ; Cognition ; Cognition Disorders/diagnosis ; Metabolic Diseases/complications ; Dementia/diagnosis
Language	English
Publishing date	2023-10-16
Publishing country	United States
Document type	Journal Article
ZDB-ID	410187-X
ISSN	0065-2598
ISSN	0065-2598
DOI	10.1007/978-3-031-42003-0_5
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 3192: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Einzelsignatur: Show issues

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Increasing demand for point-of-care testing and the potential to incorporate the Internet of medical things in an integrated health management system.

Karako, Kenji / Song, Peipei / Chen, Yu / Tang, Wei

Bioscience trends

2022 Volume 16, Issue 1, Page(s) 4–6

Abstract: As the number of people with COVID-19 increases daily around the world, point-of-care testing (POCT) is gaining attention as a tool that can provide immediate test results and greatly help to deter infection and determine what to do next. POCT has ... ...

Abstract	As the number of people with COVID-19 increases daily around the world, point-of-care testing (POCT) is gaining attention as a tool that can provide immediate test results and greatly help to deter infection and determine what to do next. POCT has several drawbacks such as a low sensitivity and specificity, but according to studies POCT has increased sensitivity on par with that of polymerase chain reaction testing. The advantage of POCT is that the results can be obtained quickly, regardless of the location. To further enhance its benefits, POCT is being developed and researched in conjunction with the Internet of medical things (IoMT), which allows POCT results to be collected, recorded, and managed over a network. IoMT will be beneficial not only for the use of POCT simply as a testing tool but also for its integration into diagnostic and health management systems. IoMT will enable people to regularly receive their test results in their daily lives and to provide personalized diagnosis and treatment of individual conditions, which will be beneficial in terms of disease prevention and maintenance of health.
MeSH term(s)	COVID-19/diagnosis ; Humans ; Internet ; Point-of-Care Testing ; SARS-CoV-2 ; Sensitivity and Specificity
Language	English
Publishing date	2022-02-22
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2543899-2
ISSN	1881-7823 ; 1881-7823
ISSN (online)	1881-7823
ISSN	1881-7823
DOI	10.5582/bst.2022.01074
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

To top

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito