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Founded Year



Series C | Alive

Total Raised


Last Raised

$26.78M | 5 mos ago


MICIN operates as a biotechnological company. It develops curon, a smart clinic platform application that enables users to remotely connect with doctors and receive medical examinations and prescriptions. The company was founded in 2015 and is based in Tokyo, Japan.

Headquarters Location

2-6-2 Otemachi, Chiyoda-ku 13th floor of Japan Building

Tokyo, 100-0004,




MICIN's Product Videos

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MICIN's Products & Differentiators


    telemedicine service


Expert Collections containing MICIN

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

MICIN is included in 2 Expert Collections, including Digital Health.


Digital Health

10,804 items

The digital health collection includes vendors developing software, platforms, sensor & robotic hardware, health data infrastructure, and tech-enabled services in healthcare. The list excludes pureplay pharma/biopharma, sequencing instruments, gene editing, and assistive tech.



2,856 items

Companies developing, offering, or using electronic and telecommunication technologies to facilitate the delivery of health & wellness services from a distance. *Columns updated as regularly as possible; priority given to companies with the most and/or most recent funding.

Latest MICIN News

Reliability of Telepsychiatry Assessments Using the Attention-Deficit/Hyperactivity Disorder Rating Scale-IV for Children With Neurodevelopmental Disorders and Their Caregivers: Randomized Feasibility Study

Feb 19, 2024

Journal of Medical Internet Research This paper is in the following e-collection/theme issue: August 10, 2023 . Reliability of Telepsychiatry Assessments Using the Attention-Deficit/Hyperactivity Disorder Rating Scale-IV for Children With Neurodevelopmental Disorders and Their Caregivers: Randomized Feasibility Study Reliability of Telepsychiatry Assessments Using the Attention-Deficit/Hyperactivity Disorder Rating Scale-IV for Children With Neurodevelopmental Disorders and Their Caregivers: Randomized Feasibility Study Authors of this article: 2Department of Child Psychiatry, Shimada Ryoiku Medical Center for Challenged Children, Tokyo, Japan 3Department of Child and Adolescent Mental Health, Aiiku Clinic, Tokyo, Japan 4Department of Child and Adolescent Psychiatry, Tokyo Metropolitan Children's Medical Center, Tokyo, Japan 5Tsurugaoka Garden Hospital, Tokyo, Japan 6Hiratsuka City Hospital, Kanagawa, Japan 7Department of Clinical Psychology, Taisho University, Tokyo, Japan 8Hills Joint Research Laboratory for Future Preventive Medicine and Wellness, Keio University School of Medicine, Tokyo, Japan Corresponding Author: Keio University School of Medicine Mori JP Tower F7 Abstract Background: Given the global shortage of child psychiatrists and barriers to specialized care, remote assessment is a promising alternative for diagnosing and managing attention-deficit/hyperactivity disorder (ADHD). However, only a few studies have validated the accuracy and acceptability of these remote methods. Objective: This study aimed to test the agreement between remote and face-to-face assessments. Methods: Patients aged between 6 and 17 years with confirmed Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition diagnoses of ADHD or autism spectrum disorder (ASD) were recruited from multiple institutions. In a randomized order, participants underwent 2 evaluations, face-to-face and remotely, with distinct evaluators administering the ADHD Rating Scale-IV (ADHD-RS-IV). Intraclass correlation coefficient (ICC) was used to assess the reliability of face-to-face and remote assessments. Results: The participants included 74 Japanese children aged between 6 and 16 years who were primarily diagnosed with ADHD (43/74, 58%) or ASD (31/74, 42%). A total of 22 (30%) children were diagnosed with both conditions. The ADHD-RS-IV ICCs between face-to-face and remote assessments showed “substantial” agreement in the total ADHD-RS-IV score (ICC=0.769, 95% CI 0.654-0.849; P<.001) according to the Landis and Koch criteria. The ICC in patients with ADHD showed “almost perfect” agreement (ICC=0.816, 95% CI 0.683-0.897; P<.001), whereas in patients with ASD, it showed “substantial” agreement (ICC=0.674, 95% CI 0.420-0.831; P<.001), indicating the high reliability of both methods across both conditions. Conclusions: Our study validated the feasibility and reliability of remote ADHD testing, which has potential benefits such as reduced hospital visits and time-saving effects. Our results highlight the potential of telemedicine in resource-limited areas, clinical trials, and treatment evaluations, necessitating further studies to explore its broader application. Trial Registration: UMIN Clinical Trials Registry UMIN000039860; J Med Internet Res 2024;26:e51749 gADHD-RS-IV, Attention-deficit/Hyperactivity Disorder Rating Scale-IV. Participants were asked how long the waiting period was until the first visit for a child psychiatrist appointment, and the average was found to be 79.0 (SD 57.1; range 1-200) days. Regarding their usual visits, it took 36.8 (SD 20.7; range 5-100) minutes from leaving home to arriving at the hospital. The average waiting time for a usual appointment was 24.0 (SD 14.6; range 5-60) minutes. The potential time that could be saved using remote visits (by adding visiting time × 2 and waiting time) was 97.7 (SD 42.5; range 40-260) minutes. ICCs of ADHD-RS-IV Between Face-to-Face and Remote Assessments The ICCs obtained after preliminary training were as follows: 0.987 (95% CI 0.934-0.999; P<.001) for the total score; 0.991 (95% CI 0.957-0.999; P<.001) for the hyperactivity/impulsivity subscore; and 0.807 (95% CI 0.022-0.978; P=.02) for the inattention subscore. The ICCs are shown in Figures 1 - 3 . The ICC of the total ADHD-RS-IV was 0.769 (95% CI 0.654-0.849; P<.001), which was “substantial,” according to the Landis and Koch criteria [ 25 ]. The ICC of the ADHD-RS-IV hyperactivity/impulsiveness and inattention subscores were 0.779 (95% CI 0.669-0.856; P<.001) and 0.667 (95% CI 0.515-0.778; P<.001), respectively, indicating “substantial” agreement. In patients with ADHD as their primary diagnosis, the ICC for total score was 0.816 (95% CI 0.683-0.897; P<.001), indicating “almost perfect” agreement; the ICC for hyperactivity/impulsiveness was 0.861 (95% CI 0.756-0.923; P<.001), indicating “almost perfect” agreement; and the ICC for inattention score was 0.642 (95% CI 0.423-0.790; P<.001), indicating “substantial” agreement. In patients with ASD as their primary diagnosis, the ICC for total score was 0.674 (95% CI 0.420-0.831; P<.001), indicating “substantial” agreement; the ICC for hyperactivity/impulsiveness was 0.591 (95% CI 0.299-0.782; P<.001), indicating “moderate” agreement; and ICC for inattention score was 0.733 (95% CI 0.511-0.863; P<.001), indicating “substantial” agreement. ‎ Figure 1. Intraclass correlations of total Attention-Deficit/Hyperactivity Disorder Rating Scale-IV (ADHD-RS-IV) score between face-to-face and remote assessments in all participants (autism spectrum disorder [ASD] and attention-deficit/hyperactivity disorder [ADHD]). ‎ Figure 2. Intraclass correlations of Attention-Deficit/Hyperactivity Disorder Rating Scale-IV (ADHD-RS-IV) hyperactivity/impulsiveness subscore between face-to-face and remote assessments in all participants (autism spectrum disorder [ASD] and attention-deficit/hyperactivity disorder [ADHD]). ‎ Figure 3. Intraclass correlations of Attention-Deficit/Hyperactivity Disorder Rating Scale-IV (ADHD-RS-IV) inattention subscore between face-to-face and remote assessments in all participants (autism spectrum disorder [ASD] and attention-deficit/hyperactivity disorder [ADHD]). There were no clear sex differences in the ICCs. In regard to age, comparing the older age group (≥11 years; n=37) and the younger age group (≤10 years; n=37), the ICC for total score was 0.675 (95% CI 0.464-0.814; P<.001) in the younger age group and 0.757 (95% CI 0.558-0.873; P<.001) in the older age group. The ICC for hyperactivity/impulsiveness was 0.706 (95% CI 0.509-0.833; P<.001) in the younger age group and 0.730 (95% CI 0.515-0.858; P<.001) in the older age group. The ICC for inattention score was 0.599 (95% CI 0.357-0.766; P<.001) in the younger age group and 0.659 (95% CI 0.408-0.818; P<.001) in the older age group. Discussion Principal Findings This is the largest study to date on the validation and feasibility of remote ADHD testing. We found good agreement between the remote- and face-to-face–administered ADHD-RS-IV. This study also showed significant potential benefits for children and their caregivers in terms of reducing hospital visits and waiting times. Additionally, as many as 14 (23%) out of the 61 caregivers who participated in the study had no previous experience with remote video calls; however, this did not pose a significant problem. This can be partly attributed to the staff providing detailed instructions. However, it is also possible that children who had attended internet-based classes at school because of the COVID-19 pandemic were able to provide guidance on the operation of the technology. The results showed that the agreement rate between the face-to-face and remote assessments was lower in patients with ASD than in those with ADHD, according to the ADHD-RS-IV. One possible reason for the difference in results between patients with ADHD and ASD is the variability in interpretation among caregivers and evaluators. For example, when asked, “Does it seem like the child is not listening when spoken to?” caregivers of children with ASD, who may already have limited social interaction, may readily answer “yes” or “always.” In contrast, they may consider it a symptom of autism rather than inattentiveness related to ADHD and answer “no.” The wide range of interpretations provided by caregivers and evaluators may be a contributing factor [ 27 ]. The ADHD-RS-IV results indicated that the inattention ICC scores were numerically lower than the hyperactivity scores. This may be due to the remote assessment environment. At the time of enrollment, a quiet environment was recommended for remote assessments. However, because of the space and density of patients’ homes, situations often arose where there were numerous stimuli, such as the presence of toys or the assessment interview being conducted while other siblings were nearby or in the same room. These circumstances, compared with a controlled hospital consultation room, may have influenced the raters’ impressions of the participants in remote assessments. Moreover, when assessments take place at home, caregivers may feel uncomfortable explaining the severe or negative condition of their children in the presence of their child or other family members. It would be desirable to confirm in advance whether a space can be secured or a time when no other siblings are present can be arranged for remote assessment. Our results have shown higher agreement rates in the older age group (≥11 years) compared to the younger age group (≤10 years). Symptoms such as hyperactivity and inattention in younger children may be more apparent in their home environment than in controlled settings due to familiarity and less stimulation control, resulting in a slight decrease in agreement with the assessment. Although there may be a benefit to internet-based assessment in regard to observing how the child typically behaves in relaxed homes, older children may be better suited for remote assessment in terms of agreement with face-to-face evaluation. The potential time-saving effect, considering the time for visits to the hospital and waiting time at the hospital, was found to be 97.7 (SD 42.5; range 40-260) minutes. Given the increase in dual-income households in Japan, which has resulted in less time being spent with children, it would be highly meaningful if we could save this amount of time using remote assessments without reducing quality. In addition, this research was conducted during the COVID-19 pandemic (the state of emergency was first declared on March 13, 2020, and was removed from the special measures law on May 8, 2023), which may have influenced the results. Although telemedicine was introduced in Japan, it was not widely adopted because of reluctance from the perspective of medical fees. Therefore, in many cases, people had to go to the hospital, facing the risk and anxiety of infection. The importance of having such tools ready to prepare for future outbreaks cannot be overlooked. While the demand for and evidence of telemedicine are expanding, there are also challenges. Issues such as the digital divide, which refers to the disparity that arises between people who can use the internet and computers and those who cannot, and in Japan specifically, the difficulty in widespread adoption due to regulations preventing billing for such services, are notable. Based on the results of our study, telemedicine may be used under the following conditions: (1) in areas where there is a shortage of medical resources, such as public health and developmental support centers, by collaborating with child psychiatrists, clinical psychologists, and other medical professionals; (2) in central evaluations in clinical trials; and (3) to evaluate treatment effectiveness by combining and complementing face-to-face visits. Although further studies are needed, it may be used to screen children and their parents who are unsure whether to see a specialist and to provide assessment support for clinics without developmental testing capabilities. Nevertheless, a careful balance must be maintained, as direct in-person assessment provides advantages such as observing nonverbal cues and behaviors, which may be important for a comprehensive understanding of the child’s condition. Limitations This study had several limitations. First, it was limited to children who had already been diagnosed and had received medical care and treatment. Therefore, these results do not apply to undiagnosed neurotypes. This study aimed to explore whether remote assessment tools could be helpful when children with developmental issues and their caregivers seek medical assistance. Therefore, the study design did not encompass typically developing children. Nonetheless, ICC, which usually tends to exhibit higher values when there is a diverse range of patient scores, manifested a relatively high degree of agreement, specifically in the group of children affected in this study. This can be interpreted as endorsing the validity of remote assessment procedures in this context. Second, although our study effectively indicated the potential for high-accuracy remote assessments, this does not necessarily guarantee a remote diagnosis. However, considering the frequent use of the ADHD-RS-IV in the diagnostic process for ADHD, the fact that we have demonstrated its robustness in the context of remote assessment may suggest its utility for future diagnoses. Even if remote ADHD-RS-IV assessments do not replace diagnosis during the first visit, they can be used to identify individuals who should be prioritized for early assessment by conducting severity evaluations and triages, thus expediting their initial consultation. To compensate for the weaknesses of this study, future studies should focus on examining the congruence between severity assessments and diagnoses conducted remotely in comparison with in-person evaluations, in addition to evaluating the efficacy of remote methods across diverse subpopulations. Comparison With Previous Work There have been few studies comparing ADHD assessment scales in face-to-face and remote settings. In previous research in the field of neurodevelopmental disorders, there is a report on the usability and reliability of the Autism Diagnostic Observation Schedule conducted face-to-face and remotely with 23 adults with ASD [ 16 ]. The ICC between face-to-face and remote was high at 0.92. In their report, technicians were present in the room during the remote assessment to provide assistance with technical operations, whereas in this study, we made it possible for participants to operate the equipment themselves at home without the help of technicians. Additionally, in that study, the same examiner conducted the tests in both face-to-face and remote settings for all cases. In contrast, in our study, different examiners conducted the tests in face-to-face and remote settings. Although it is difficult to compare because the disorder and assessment tools are different, considering these factors, the ICC value of our results is comparable, indicating a new finding in this field. Conclusions The results of this study showed that developmental assessments can be conducted with the same level of accuracy using remote tools as compared to face-to-face assessments. This means that even medical institutions where specialized assessments are not available, as well as health care centers, can benefit from these assessments, thereby improving the convenience for children who require early detection and intervention. Future research is needed to investigate the consistency of remote assessments and diagnoses compared with the initial face-to-face examination as well as the effectiveness of remote examinations in various subpopulations. Acknowledgments This study was supported in part by the Japan Science and Technology Agency Program on Open Innovation Platform With Enterprises, Research Institute, and Academia (JST-OPERA; grant JPMJOP1842; Principal Investigator Hiroaki Miyata) and by MICIN Inc, Tokyo, Japan. Conflicts of Interest KN has received speaker’s honoraria from Takeda, Janssen, Eli Lilly, Eisai, MSD, Otsuka, and Shionogi. MK has received honoraria from Takeda and Shionogi. TK has received consultant fees from Dainippon Sumitomo, Novartis, and Otsuka; speaker’s honoraria from Banyu, Eli Lilly, Dainippon Sumitomo, Janssen, MSD, Novartis, Otsuka, and Pfizer; and grant support from Takeda, Dainippon-Sumitomo, and Otsuka. The remaining authors have no conflicts of interest to declare. References Dawson G, Rogers S, Munson J, Smith M, Winter J, Greenson J, et al. Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model. Pediatrics. 2010;125(1):e17-e23. [ FREE Full text ] [ CrossRef ] [ Medline ] Kamio Y, Inada N, Koyama T. A nationwide survey on quality of life and associated factors of adults with high-functioning autism spectrum disorders. Autism. 2013;17(1):15-26. [ CrossRef ] [ Medline ] Halperin JM, Marks DJ. Practitioner review: assessment and treatment of preschool children with attention-deficit/hyperactivity disorder. J Child Psychol Psychiatry. 2019;60(9):930-943. [ CrossRef ] [ Medline ] Zablotsky B, Black LI, Maenner MJ, Schieve LA, Danielson ML, Bitsko RH, et al. Prevalence and trends of developmental disabilities among children in the United States: 2009-2017. Pediatrics. 2019;144(4):e20190811. [ FREE Full text ] [ CrossRef ] [ Medline ] Nakamura S, Ohnishi M, Uchiyama S. Epidemiological survey of adult attention deficit hyperactivity disorder (ADHD) in Japan. Jpn J Psychiatr Treat. 2013;28:155-162. Penner M, Anagnostou E, Ungar WJ. Practice patterns and determinants of wait time for autism spectrum disorder diagnosis in Canada. Mol Autism. 2018;9:16. [ FREE Full text ] [ CrossRef ] [ Medline ] McKenzie K, Forsyth K, O'Hare A, McClure I, Rutherford M, Murray A, et al. Factors influencing waiting times for diagnosis of autism spectrum disorder in children and adults. Res Dev Disabil. 2015;45-46:300-306. [ CrossRef ] [ Medline ] McCarthy S, Asherson P, Coghill D, Hollis C, Murray M, Potts L, et al. Attention-deficit hyperactivity disorder: treatment discontinuation in adolescents and young adults. Br J Psychiatry. 2009;194(3):273-277. [ FREE Full text ] [ CrossRef ] [ Medline ] Nomura K, Tarumi R, Yoshida K, Sado M, Suzuki T, Mimura M, et al. Cancellation of outpatient appointments in patients with attention-deficit/hyperactivity disorder. PLoS One. 2021;16(11):e0260431. [ FREE Full text ] [ CrossRef ] [ Medline ] National Institute for Health and Care Excellence (UK). Attention Deficit Hyperactivity Disorder: Diagnosis and Management. London. National Institute for Health and Care Excellence (NICE); 2019. Pliszka S, AACAP Work Group on Quality Issues. Practice parameter for the assessment and treatment of children and adolescents with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2007;46(7):894-921. [ FREE Full text ] [ CrossRef ] [ Medline ] Stevens J, Quittner AL, Abikoff H. Factors influencing elementary school teachers' ratings of ADHD and ODD behaviors. J Clin Child Psychol. 1998;27(4):406-414. [ CrossRef ] [ Medline ] Simonoff E, Pickles A, Hervas A, Silberg JL, Rutter M, Eaves L. Genetic influences on childhood hyperactivity: contrast effects imply parental rating bias, not sibling interaction. Psychol Med. 1998;28(4):825-837. [ CrossRef ] [ Medline ] Kobak KA, Leuchter A, DeBrota D, Engelhardt N, Williams JBW, Cook IA, et al. Site versus centralized raters in a clinical depression trial: impact on patient selection and placebo response. J Clin Psychopharmacol. 2010;30(2):193-197. [ CrossRef ] [ Medline ] Kane JM, Robinson DG, Schooler NR, Mueser KT, Penn DL, Rosenheck RA, et al. Comprehensive versus usual community care for first-episode psychosis: 2-year outcomes from the NIMH RAISE Early Treatment Program. Am J Psychiatry. 2016;173(4):362-372. [ FREE Full text ] [ CrossRef ] [ Medline ] Ward-King J, Cohen IL, Penning H, Holden JJA. Brief report: telephone administration of the autism diagnostic interview—revised: reliability and suitability for use in research. J Autism Dev Disord. 2010;40(10):1285-1290. [ CrossRef ] [ Medline ] Schutte JL, McCue MP, Parmanto B, McGonigle J, Handen B, Lewis A, et al. Usability and reliability of a remotely administered adult autism assessment, the Autism Diagnostic Observation Schedule (ADOS) Module 4. Telemed J E Health. 2015;21(3):176-184. [ FREE Full text ] [ CrossRef ] [ Medline ] Smith CJ, Rozga A, Matthews N, Oberleitner R, Nazneen N, Abowd G. Investigating the accuracy of a novel telehealth diagnostic approach for autism spectrum disorder. Psychol Assess. 2017;29(3):245-252. [ FREE Full text ] [ CrossRef ] [ Medline ] DuPaul G, Power TJ, Anastopoulos AD, Reid R. ADHD Rating Scale-IV : Checklists, Norms, and Clinical Interpretation. New York. Guilford Press; 1998. Tani I, Okada R, Ohnishi M, Nakajima S, Tsujii M. Japanese version of home form of the ADHD-RS: an evaluation of its reliability and validity. Res Dev Disabil. 2010;31(6):1426-1433. [ CrossRef ] [ Medline ] McGough JJ, Sturm A, Cowen J, Tung K, Salgari GC, Leuchter AF, et al. Double-blind, sham-controlled, pilot study of trigeminal nerve stimulation for attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2019;58(4):403-411.e3. [ FREE Full text ] [ CrossRef ] [ Medline ] Riggs PD, Winhusen T, Davies RD, Leimberger JD, Mikulich-Gilbertson S, Klein C, et al. Randomized controlled trial of osmotic-release methylphenidate with cognitive-behavioral therapy in adolescents with attention-deficit/hyperactivity disorder and substance use disorders. J Am Acad Child Adolesc Psychiatry. 2011;50(9):903-914. [ FREE Full text ] [ CrossRef ] [ Medline ] Takayanagi N, Yoshida S, Yasuda S, Adachi M, Kaneda-Osato A, Tanaka M, et al. Psychometric properties of the Japanese ADHD-RS in preschool children. Res Dev Disabil. 2016;55:268-278. [ CrossRef ] [ Medline ] American Psychiatric Association; American Psychiatric Association DSM-5 Task Force. Diagnostic and statistical manual of mental disorders DSM-5, 5th Edition. Washington, DC. American Psychiatric Association; 2013. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159-174. [ Medline ] Doros G, Lew R. Design based on intra-class correlation coefficients. Curr J Biostat. 2010;1(1):1-8. [ CrossRef ] Grzadzinski R, Dick C, Lord C, Bishop S. Parent-reported and clinician-observed autism spectrum disorder (ASD) symptoms in children with attention deficit/hyperactivity disorder (ADHD): implications for practice under DSM-5. Mol Autism. 2016;7:7. [ FREE Full text ] [ CrossRef ] [ Medline ] ‎

MICIN Frequently Asked Questions (FAQ)

  • When was MICIN founded?

    MICIN was founded in 2015.

  • Where is MICIN's headquarters?

    MICIN's headquarters is located at 2-6-2 Otemachi, Chiyoda-ku, Tokyo.

  • What is MICIN's latest funding round?

    MICIN's latest funding round is Series C.

  • How much did MICIN raise?

    MICIN raised a total of $36.82M.

  • Who are the investors of MICIN?

    Investors of MICIN include Alfresa Holdings Corporation, World Innovation Lab, MTG Ventures, Toho Holdings Co. Ltd., Aozora Investment and 9 more.

  • Who are MICIN's competitors?

    Competitors of MICIN include Integrity Healthcare and 1 more.

  • What products does MICIN offer?

    MICIN's products include curon and 4 more.

  • Who are MICIN's customers?

    Customers of MICIN include Yamashita clinic, MIYAZAKI RC Clinic, TOKYO Medical Association and Hiroshima prefecture.


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