764 results match your criteria: "Center for Advanced Intelligence Project[Affiliation]"

In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the selection of appropriate computational models is critical for accurate diagnosis and patient care. This literature review provides a comprehensive comparison of vision transformers (ViTs) and convolutional neural networks (CNNs), the two leading techniques in the field of deep learning in medical imaging. We conducted a survey systematically.

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  • High-throughput phenotyping can streamline breeding cycles and reduce costs, focusing on biomass-related traits in soybean using UAV remote sensing and deep learning.
  • In a 2018 field experiment with 198 soybean accessions, a convolutional neural network (CNN) was used to accurately estimate traits like dry weight and plant height from UAV-collected data.
  • The study showed that deep learning could identify strong correlations between input data and phenotypic traits, highlighting the potential use of these insights in improving breeding practices.
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Whether all obesity-related variants contribute to the onset of obesity or one or a few variants cause obesity in genetically heterogeneous populations remains obscure. Here, we investigated the genetic architecture of obesity by clustering the Japanese and British populations with obesity using obesity-related factors. In Step-1, we conducted a genome-wide association study (GWAS) with body mass index (BMI) as the outcome for eligible participants.

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Background: The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease.

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Objective: The 2023 International Federation of Gynecology and Obstetrics classification with molecular classification shows superior discriminatory ability compared to staging systems lacking molecular data. However, the accuracy of endometrial biopsy data in molecular classification remains uncertain. This study aimed to assess the concordance of molecular classifications between preoperative biopsy and hysterectomy to predict prognosis before surgical staging.

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Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) (1-3). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs.

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The analysis of complex behavior in empirical data poses significant challenges in various scientific and engineering disciplines. Dynamic Mode Decomposition (DMD) is a widely used method to reveal the spectral features of nonlinear dynamical systems without prior knowledge. However, because of its infinite dimensions, analyzing the continuous spectrum resulting from chaos and noise is problematic.

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  • Neuroimaging databases for neuro-psychiatric disorders provide valuable data for researchers to explore diseases, develop machine learning models, and redefine understanding of these conditions.* ! -
  • A review identified 42 global MRI datasets totaling 23,293 samples from patients with various disorders, including mood, developmental, schizophrenia, Parkinson's, and dementia.* ! -
  • Improved governance and addressing technical issues of these databases are essential for sharing data across borders, aiding in understanding, diagnosing, and creating early interventions for neuro-psychiatric disorders.* !
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Psychological resilience is positively correlated with Habenula volume.

J Affect Disord

November 2024

Department of Neuropsychiatry, Graduate School of Medicine, University of Kyoto, Kyoto, Japan; Artificial Intelligence Ethics and Society Team, RIKEN Center for Advanced Intelligence Project, Saitama, Japan; The General Research Division, Osaka University Research Center on Ethical, Legal and Social Issues, Kyoto, Japan. Electronic address:

Article Synopsis
  • The study examines the link between the volume of the Habenula (Hb), a brain region related to stress, and psychological resilience in healthy adults, exploring how these factors relate to depressive tendencies.
  • Results indicate a positive correlation between Hb volume and resilience, particularly in women, suggesting that higher Hb volume may associate with better resilience.
  • The findings propose that resilience mediates the relationship between Hb volume and depression, indicating that even those without clinical depression can experience these dynamics in relation to their brain structure.
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Background: Frailty is a multifactorial syndrome; through this study, we aimed to investigate the physiological, psychological, and social factors associated with frailty and frailty worsening in community-dwelling older adults.

Methods: We conducted a cross-sectional and longitudinal study using data from the "Community Empowerment and Well-Being and Healthy Long-term Care: Evidence from a Cohort Study (CEC)," which focuses on community dwellers aged 65 and above in Japan. The sample of the cross-sectional study was drawn from a CEC study conducted in 2014 with a total of 673 participants.

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  • Sleep quality is vital for health, and EEG signals help analyze sleep status for better medical guidance.
  • The study introduces an artificial data generation method to enhance small real data sets, achieving a classification model with 92.85% accuracy.
  • By combining augmented data with a public database and using EEGNet, the research overcomes challenges of subject-independent analysis, allowing effective use of limited labeled data for personalized sleep analysis.
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  • Peritoneal washing cytology (CY) is primarily used for staging pancreatic cancer and assessing intraperitoneal status for better prognosis predictions.
  • This study explored using deep learning techniques like Vision Transformer (ViT) and Convolutional Neural Network (CNN) to analyze CY specimen images from 88 patients to predict their 1-year survival rates.
  • The findings revealed that both AI models had high accuracy in prognosis prediction, with ViT being slightly more effective, and identified neutrophils as a potential negative prognostic marker for these patients.
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It remains difficult for mobile robots to continue accurate self-localization when they are suddenly teleported to a location that is different from their beliefs during navigation. Incorporating insights from neuroscience into developing a spatial cognition model for mobile robots may make it possible to acquire the ability to respond appropriately to changing situations, similar to living organisms. Recent neuroscience research has shown that during teleportation in rat navigation, neural populations of place cells in the cornu ammonis-3 region of the hippocampus, which are sparse representations of each other, switch discretely.

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The adenosine A receptor (AR) engages several G proteins, notably G and its cognate G protein. This coupling promiscuity is facilitated by a dynamic ensemble, revealed by F nuclear magnetic resonance imaging of AR and G protein. Two transmembrane helix 6 (TM6) activation states, formerly associated with partial and full agonism, accommodate the differing volumes of G and G.

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Elimination of the extra chromosome of Dup15q syndrome iPSCs for cellular and molecular investigation.

Eur J Cell Biol

September 2024

Center for iPS Cell Research and Application (CiRA), Kyoto University, 53 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan; Takeda-CiRA (T-CiRA) Joint Program, 2-26-1, Muraoka-Higashi, Fujisawa 251-8555, Japan; iPSC-based Drug discovery and Development Team, RIKEN BioResource Research Center, 1-7 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0237, Japan; Medical-Risk Avoidance based on iPS Cells Team, RIKEN Center for Advanced Intelligence Project (AIP), 53 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan. Electronic address:

Chromosome 15q11.2-13.1 duplication (Dup15q) syndrome is one of the most common autism spectrum disorders (ASDs) associated with copy number variants (CNVs).

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The UPPS-P Impulsive Behavior Model and the various psychometric instruments developed and validated based on this model are well established in clinical and research settings. However, evidence regarding the psychometric validity, reliability, and equivalence across multiple countries of residence, languages, or gender identities, including gender-diverse individuals, is lacking to date. Using data from the International Sex Survey ( = 82,243), confirmatory factor analyses and measurement invariance analyses were performed on the preestablished five-factor structure of the 20-item short version of the UPPS-P Impulsive Behavior Scale to examine whether (a) psychometric validity and reliability and (b) psychometric equivalence hold across 34 country-of-residence-related, 22 language-related, and three gender-identity-related groups.

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Complex chromosomal 6q rearrangements revealed by combined long-molecule genomics technologies.

Genomics

September 2024

Department of Human Genetics, Yokohama City University Graduate School of Medicine, Yokohama 236-0004, Japan; Department of Rare Disease Genomics, Yokohama City University Hospital, Yokohama 236-0004, Japan; Department of Clinical Genetics, Yokohama City University Hospital, Yokohama 236-0004, Japan. Electronic address:

Technologies for detecting structural variation (SV) have advanced with the advent of long-read sequencing, which enables the validation of SV at a nucleotide level. Optical genome mapping (OGM), a technology based on physical mapping, can also provide comprehensive SVs analysis. We applied long-read whole genome sequencing (LRWGS) to accurately reconstruct breakpoint (BP) segments in a patient with complex chromosome 6q rearrangements that remained elusive by conventional karyotyping.

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Can physician judgment enhance model trustworthiness? A case study on predicting pathological lymph nodes in rectal cancer.

Artif Intell Med

August 2024

Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan. Electronic address:

Explainability is key to enhancing the trustworthiness of artificial intelligence in medicine. However, there exists a significant gap between physicians' expectations for model explainability and the actual behavior of these models. This gap arises from the absence of a consensus on a physician-centered evaluation framework, which is needed to quantitatively assess the practical benefits that effective explainability should offer practitioners.

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Construction of multilayered small intestine-like tissue by reproducing interstitial flow.

Cell Stem Cell

September 2024

Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto 606-8507, Japan; AMED-CREST, Japan Agency for Medical Research and Development (AMED), Tokyo 100-0004, Japan. Electronic address:

Recent advances have made modeling human small intestines in vitro possible, but it remains a challenge to recapitulate fully their structural and functional characteristics. We suspected interstitial flow within the intestine, powered by circulating blood plasma during embryonic organogenesis, to be a vital factor. We aimed to construct an in vivo-like multilayered small intestinal tissue by incorporating interstitial flow into the system and, in turn, developed the micro-small intestine system by differentiating definitive endoderm and mesoderm cells from human pluripotent stem cells simultaneously on a microfluidic device capable of replicating interstitial flow.

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Background: Social communication is a key factor in maintaining cognitive function and contributes to well-being in later life.

Objective: This study will examine the effects of "Photo-Integrated Conversation Moderated by Application version 2" (PICMOA-2), which is a web-based conversational intervention, on cognitive performance, frailty, and social and psychological indicators among community-dwelling older adults.

Methods: This study is a randomized controlled trial with an open-label, 2-parallel group trial and 1:1 allocation design.

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Profiling and assessing the risks of image- and performance-enhancing drugs use during the COVID-19 lockdown.

Front Public Health

July 2024

Department of Clinical, Pharmaceutical and Biological Sciences, School of Life and Medical Sciences, University of Hertfordshire, Hatfield, United Kingdom.

Background: Image and Performance-Enhancing Drugs (IPEDs) can enhance mental and physical capabilities and impact one's overall health. Initially confined in sport environments, IPEDs use has become increasingly widespread in a high-performing society. The present study was aimed at profiling IPEDs use during the COVID-19 lockdown among an international sample of young adults.

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No study, to our knowledge, has constructed a polygenic risk score based on clinical blood pressure and investigated the association of genetic and lifestyle risks with home hypertension. We examined the associations of combined genetic and lifestyle risks with hypertension and home hypertension. In a cross-sectional study of 7027 Japanese individuals aged ≥20 years, we developed a lifestyle score based on body mass index, alcohol consumption, physical activity, and sodium-to-potassium ratio, categorized into ideal, intermediate, and poor lifestyles.

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Article Synopsis
  • The study assessed how genetic risk factors and lifestyle choices influence the likelihood of developing diabetes in a group of over 11,000 individuals aged 20 and older.
  • Results showed that both genetic risk and lifestyle played significant roles in diabetes development, with an increased risk for those with low genetic risk but poor lifestyle habits.
  • The findings emphasize the importance of maintaining a healthy lifestyle for diabetes prevention, regardless of genetic predisposition, and suggest that genetic data can enhance risk stratification beyond lifestyle and family history.
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