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1.
J Chin Med Assoc ; 2021 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-34596082

RESUMO

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic continues to affect countries worldwide. To inhibit the transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), testing of patients, contact tracing, and quarantine of their close contacts have been used as major non-pharmaceutical interventions. The advantages of antigen tests, such as low cost and rapid turnaround, may allow for the rapid identification of larger numbers of infectious persons. This meta-analysis aimed to evaluate the diagnostic accuracy of antigen tests for SARS-CoV-2. METHODS: We searched PubMed, Embase, Cochrane Library, and Biomed Central databases from inception to January 2, 2021. Studies evaluating the diagnostic accuracy of antigen testing for SARS-CoV-2 with reference standards were included. We included studies that provided sufficient data to construct a 2 × 2 table on a per-patient basis. Only articles in English were reviewed. Summary sensitivity and specificity for antigen tests were generated using a random-effects model. RESULTS: Fourteen studies with 8,624 participants were included. The meta-analysis for antigen testing generated a pooled sensitivity of 79% (95% CI: 66-88%; 14 studies, 8,624 patients) and a pooled specificity of 100% (95% CI: 99-100%; 14 studies, 8,624 patients). The subgroup analysis of studies that reported specimen collection within 7 days after symptom onset showed a pooled sensitivity of 95% (95% CI: 78-99%; 4 studies, 1,342 patients) and pooled specificity of 100% (95% CI: 97-100%; 4 studies, 1,342 patients). Regarding the applicability, the patient selection, index tests, and reference standards of studies in our meta-analysis matched the review title. CONCLUSION: Antigen tests have moderate sensitivity and high specificity for the detection of SARS-CoV-2. Antigen tests might have a higher sensitivity in detecting SARS-CoV-2 within 7 days after symptom onset. Based on our findings, antigen testing might be an effective method for identifying contagious individuals to block SARS-CoV-2 transmission.

2.
J Chin Med Assoc ; 2021 Oct 08.
Artigo em Inglês | MEDLINE | ID: mdl-34643619

RESUMO

Electrotherapy or electrical stimulation (ES) is a part of clinical intervention in the rehabilitation field. With rehabilitation intervention, electrotherapy may be provided as a treatment for pain relief, strengthening, muscle education, wound recovery, or functional training. Although these interventions may not be considered as the primary therapy for patients, the advantages of the ease of operation, lower costs, and lower risks render ES to be applied frequently in clinics. There have also been emerging ES tools for brain modulation in the past decade. ES interventions are not only considered analgesics but also as an important assistive therapy for motor improvement in orthopedic and neurological rehabilitation. In addition, during the coronavirus disease pandemic, lockdowns and self-quarantine policies have led to the discontinuation of orthopedic and neurological rehabilitation interventions. Therefore, the feasibility and effectiveness of home-based electrotherapy may provide opportunities for the prevention of deterioration or extension of the original therapy. The most common at-home applications in previous studies showed positive effects on pain relief, functional ES, muscle establishment, and motor training. Currently, there is a lack of certain products for at-home brain modulation; however, transcranial direct current stimulation has shown the potential of future home-based rehabilitation due to its relatively small and simple design. We have organized the features and applications of ES tools and expect the future potential of remote therapy during the viral pandemic.

3.
J Chin Med Assoc ; 84(8): 754-756, 2021 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-34145198

RESUMO

Osteoarthritis (OA) is a common degenerative disease; however, its exact pathophysiology and early diagnosis are still a challenge. Growing attention to the exosomes may inspire innovations that would make the current management of OA more effective. The exosomes in synovial fluid are relatively stable, and they can be easily isolated by the relatively noninvasive procedure of liquid biopsy to provide diagnostic and monitoring value. Some miRNAs (miR-504, miR-146a, miR-26a, miR-200c, and miR-210) have been known to be secreted in exosomes of OA patients. On the other hand, intraarticular injection of platelet-rich plasma (PRP) is becoming a popular therapy for OA patients. PRP is also a source of exosomes and their numerous contents. It is evident from the literature that PRP-derived exosomes can induce chondrogenic gene expression in OA chondrocytes. Here, we review the latest findings on the roles of exosomes in OA with the emphasis on PRP-derived exosomes and their potential applications for treating OA.

4.
World J Gastroenterol ; 27(22): 2979-2993, 2021 Jun 14.
Artigo em Inglês | MEDLINE | ID: mdl-34168402

RESUMO

The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available. The advent of image-enhanced and magnifying endoscopies has highlighted the step toward perfecting endoscopic screening and diagnosis of gastric lesions. Simultaneously, with the development of convolutional neural network, artificial intelligence (AI) has made unprecedented breakthroughs in medical imaging, including the ongoing trials of computer-aided detection of colorectal polyps and gastrointestinal bleeding. In the past demi-decade, applications of AI systems in gastric cancer have also emerged. With AI's efficient computational power and learning capacities, endoscopists can improve their diagnostic accuracies and avoid the missing or mischaracterization of gastric neoplastic changes. So far, several AI systems that incorporated both traditional and novel endoscopy technologies have been developed for various purposes, with most systems achieving an accuracy of more than 80%. However, their feasibility, effectiveness, and safety in clinical practice remain to be seen as there have been no clinical trials yet. Nonetheless, AI-assisted endoscopies shed light on more accurate and sensitive ways for early detection, treatment guidance and prognosis prediction of gastric lesions. This review summarizes the current status of various AI applications in gastric cancer and pinpoints directions for future research and clinical practice implementation from a clinical perspective.


Assuntos
Inteligência Artificial , Neoplasias Gástricas , Detecção Precoce de Câncer , Endoscopia Gastrointestinal , Humanos , Redes Neurais de Computação , Neoplasias Gástricas/diagnóstico por imagem
5.
Int J Mol Sci ; 22(11)2021 May 25.
Artigo em Inglês | MEDLINE | ID: mdl-34070492

RESUMO

Inherited retinal dystrophies (IRDs) are rare but highly heterogeneous genetic disorders that affect individuals and families worldwide. However, given its wide variability, its analysis of the driver genes for over 50% of the cases remains unexplored. The present study aims to identify novel driver genes, disease-causing variants, and retinitis pigmentosa (RP)-associated pathways. Using family-based whole-exome sequencing (WES) to identify putative RP-causing rare variants, we identified a total of five potentially pathogenic variants located in genes OR56A5, OR52L1, CTSD, PRF1, KBTBD13, and ATP2B4. Of the variants present in all affected individuals, genes OR56A5, OR52L1, CTSD, KBTBD13, and ATP2B4 present as missense mutations, while PRF1 and CTSD present as frameshift variants. Sanger sequencing confirmed the presence of the novel pathogenic variant PRF1 (c.124_128del) that has not been reported previously. More causal-effect or evidence-based studies will be required to elucidate the precise roles of these SNPs in the RP pathogenesis. Taken together, our findings may allow us to explore the risk variants based on the sequencing data and upgrade the existing variant annotation database in Taiwan. It may help detect specific eye diseases such as retinitis pigmentosa in East Asia.


Assuntos
Catepsina D/genética , Predisposição Genética para Doença , Distrofias Retinianas/genética , Adulto , Idoso , Catepsina D/sangue , Feminino , Mutação da Fase de Leitura , Ontologia Genética , Humanos , Masculino , Pessoa de Meia-Idade , Proteínas Musculares/genética , Mutação de Sentido Incorreto , Linhagem , Perforina/genética , ATPases Transportadoras de Cálcio da Membrana Plasmática/genética , Polimorfismo de Nucleotídeo Único , Mapas de Interação de Proteínas , Distrofias Retinianas/congênito , Distrofias Retinianas/patologia , Retinite Pigmentosa/congênito , Retinite Pigmentosa/diagnóstico por imagem , Retinite Pigmentosa/genética , Retinite Pigmentosa/patologia , Fatores de Risco , Tomografia de Coerência Óptica , Sequenciamento Completo do Exoma
6.
Surg Endosc ; 2021 Feb 16.
Artigo em Inglês | MEDLINE | ID: mdl-33591447

RESUMO

OBJECTIVES: Computer-aided diagnosis (CAD)-based artificial intelligence (AI) has been shown to be highly accurate for detecting and characterizing colon polyps. However, the application of AI to identify normal colon landmarks and differentiate multiple colon diseases has not yet been established. We aimed to develop a convolutional neural network (CNN)-based algorithm (GUTAID) to recognize different colon lesions and anatomical landmarks. METHODS: Colonoscopic images were obtained to train and validate the AI classifiers. An independent dataset was collected for verification. The architecture of GUTAID contains two major sub-models: the Normal, Polyp, Diverticulum, Cecum and CAncer (NPDCCA) and Narrow-Band Imaging for Adenomatous/Hyperplastic polyps (NBI-AH) models. The development of GUTAID was based on the 16-layer Visual Geometry Group (VGG16) architecture and implemented on Google Cloud Platform. RESULTS: In total, 7838 colonoscopy images were used for developing and validating the AI model. An additional 1273 images were independently applied to verify the GUTAID. The accuracy for GUTAID in detecting various colon lesions/landmarks is 93.3% for polyps, 93.9% for diverticula, 91.7% for cecum, 97.5% for cancer, and 83.5% for adenomatous/hyperplastic polyps. CONCLUSIONS: A CNN-based algorithm (GUTAID) to identify colonic abnormalities and landmarks was successfully established with high accuracy. This GUTAID system can further characterize polyps for optical diagnosis. We demonstrated that AI classification methodology is feasible to identify multiple and different colon diseases.

7.
Sci Rep ; 11(1): 4229, 2021 Feb 19.
Artigo em Inglês | MEDLINE | ID: mdl-33608568

RESUMO

A single-blind study to investigate the effects of noisy galvanic vestibular stimulation (nGVS) in straight walking and 2 Hz head yaw walking for healthy and bilateral vestibular hypofunction (BVH) participants in light and dark conditions. The optimal stimulation intensity for each participant was determined by calculating standing stability on a force plate while randomly applying six graded nGVS intensities (0-1000 µA). The chest-pelvic (C/P) ratio and lateral deviation of the center of mass (COM) were measured by motion capture during straight and 2 Hz head yaw walking in light and dark conditions. Participants were blinded to nGVS served randomly and imperceivably. Ten BVH patients and 16 healthy participants completed all trials. In the light condition, the COM lateral deviation significantly decreased only in straight walking (p = 0.037) with nGVS for the BVH. In the dark condition, both healthy (p = 0.026) and BVH (p = 0.017) exhibited decreased lateral deviation during nGVS. The C/P ratio decreased significantly in BVH for 2 Hz head yaw walking with nGVS (p = 0.005) in light conditions. This study demonstrated that nGVS effectively reduced walking deviations, especially in visual deprived condition for the BVH. Applying nGVS with different head rotation frequencies and light exposure levels may accelerate the rehabilitation process for patients with BVH.Clinical Trial Registration This clinical trial was prospectively registered at www.clinicaltrials.gov with the Unique identifier: NCT03554941. Date of registration: (13/06/2018).

8.
Int J Mol Sci ; 22(3)2021 Jan 28.
Artigo em Inglês | MEDLINE | ID: mdl-33525682

RESUMO

Angiotensin-converting enzyme 2 (ACE2) was identified as the main host cell receptor for the entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its subsequent infection. In some coronavirus disease 2019 (COVID-19) patients, it has been reported that the nervous tissues and the eyes were also affected. However, evidence supporting that the retina is a target tissue for SARS-CoV-2 infection is still lacking. This present study aimed to investigate whether ACE2 expression plays a role in human retinal neurons during SARS-CoV-2 infection. Human induced pluripotent stem cell (hiPSC)-derived retinal organoids and monolayer cultures derived from dissociated retinal organoids were generated. To validate the potential entry of SARS-CoV-2 infection in the retina, we showed that hiPSC-derived retinal organoids and monolayer cultures endogenously express ACE2 and transmembrane serine protease 2 (TMPRSS2) on the mRNA level. Immunofluorescence staining confirmed the protein expression of ACE2 and TMPRSS2 in retinal organoids and monolayer cultures. Furthermore, using the SARS-CoV-2 pseudovirus spike protein with GFP expression system, we found that retinal organoids and monolayer cultures can potentially be infected by the SARS-CoV-2 pseudovirus. Collectively, our findings highlighted the potential of iPSC-derived retinal organoids as the models for ACE2 receptor-based SARS-CoV-2 infection.


Assuntos
Enzima de Conversão de Angiotensina 2/genética , COVID-19/genética , Expressão Gênica , Células-Tronco Pluripotentes Induzidas/citologia , Retina/citologia , SARS-CoV-2/fisiologia , Enzima de Conversão de Angiotensina 2/metabolismo , COVID-19/metabolismo , Técnicas de Cultura de Células , Linhagem Celular , Humanos , Células-Tronco Pluripotentes Induzidas/metabolismo , Organoides/citologia , Organoides/metabolismo , Retina/metabolismo , Serina Endopeptidases/genética , Serina Endopeptidases/metabolismo , Internalização do Vírus
9.
J Chin Med Assoc ; 84(2): 158-164, 2021 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-32858548

RESUMO

BACKGROUND: Cardiotocography is a common method of electronic fetal monitoring (EFM) for fetal well-being. Data-driven analyses have shown potential for automated EFM assessment. For this preliminary study, we used a novel artificial intelligence method based on fully convolutional networks (FCNs), with deep learning for EFM evaluation and correct recognition, and its possible role in evaluation of nonreassuring fetal status. METHODS: We retrospectively collected 3239 EFM labor records from 292 deliveries and neonatal Apgar scores between December 2018 and July 2019 at a single medical center. We analyzed these data using an FCN model and compared the results with clinical practice. RESULTS: The FCN model recognized EFM traces like physicians, with an average Cohen's kappa coefficient of agreement of 0.525 and average area under the receiver operating characteristic curve of 0.892 for six fetal heart rate (FHR) categories. The FCN model showed higher sensitivity for predicting fetal compromise (0.528 vs 0.132) but a higher false-positive rate (0.632 vs 0.012) compared with clinical practice. CONCLUSION: FCN is a modern technique that may be useful for EFM trace recognition based on its multiconvolutional layered analysis. Our model showed a competitive ability to identify FHR patterns and the potential for evaluation of nonreassuring fetal status.

10.
J Vestib Res ; 31(1): 23-32, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33325420

RESUMO

BACKGROUND: Embedded within most rapid head rotations are gaze shifts, which is an initial eye rotation to a target of interest, followed by a head rotation towards the same target. Gaze shifts are used to acquire an image that initially is outside of the participant's current field of vision. Currently, there are no tools available that evaluate the functional relevance of a gaze shift. OBJECTIVE: The purpose of our study was to measure dynamic visual acuity (DVA) while performing a gaze shift. METHODS: Seventy-one healthy participants (42.79±16.89 years) and 34 participants with unilateral vestibular hypofunction (UVH) (54.59±20.14 years) were tested while wearing an inertial measurement unit (IMU) sensor on the head and walking on a treadmill surrounded by three monitors. We measured visual acuity during three subcomponent tests: standing (static visual acuity), while performing an active head rotation gaze shift, and an active head rotation gaze shift while walking (gsDVAw). RESULTS: While doing gsDVAw, patients with Left UVH (n = 21) had scores worse (p = 0.023) for leftward (0.0446±0.0943 LogMAR) head rotation compared with the healthy controls (-0.0075±0.0410 LogMAR). Similarly, patients with right UVH (N = 13) had worse (p = 0.025) gsDVAw for rightward head motion (0.0307±0.0481 LogMAR) compared with healthy controls (-0.0047±0.0433 LogMAR). As a whole, gsDVAw scores were worse in UVH compared to the healthy controls when we included the ipsilesional head rotation on both sides gsDVAw (0.0061±0.0421 LogMAR healthy vs. 0.03926±0.0822 LogMAR UVH, p = 0.003). Controlling for age had no effect, the gsDVAw scores of the patients were always worse (p < 0.01). CONCLUSION: The gaze shift DVA test can distinguish gaze stability in patients with UVH from healthy controls. This test may be a useful measure of compensation for patients undergoing various therapies for their vestibular hypofunction.

11.
J Chin Med Assoc ; 83(12): 1102-1106, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33210900

RESUMO

BACKGROUND: Diabetic macular edema (DME) is a sight-threatening condition that needs regular examinations and remedies. Optical coherence tomography (OCT) is the most common used examination to evaluate the structure and thickness of the macula, but the software in the OCT machine does not tell the clinicians whether DME exists directly. Recently, artificial intelligence (AI) is expected to aid in diagnosis generation and therapy selection. We thus develop a smartphone-based offline AI system that provides diagnostic suggestions and medical strategies through analyzing OCT images from diabetic patients at the risk of developing DME. METHODS: DME patients receiving treatments in 2017 at Taipei Veterans General Hospital were included in this study. We retrospectively collected the OCT images of these patients from January 2008 to July 2018. We established the AI model based on MobileNet architecture to classify the OCT images conditions. The confusion matrix has been applied to present the performance of the trained AI model. RESULTS: Based on the convolutional neural network with the MobileNet model, our AI system achieved a high DME diagnostic accuracy of 90.02%, which is comparable to other AI systems such as InceptionV3 and VGG16. We further developed a mobile-application based on this AI model available at https://aicl.ddns.net/DME.apk. CONCLUSION: We successful integrated an AI model into the mobile device to provide an offline method to provide the diagnosis for quickly screening the risk of developing DME. With the offline property, our model could help those nonophthalmological healthcare providers in offshore islands or underdeveloped countries.

12.
Brain Sci ; 10(10)2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-33076417

RESUMO

Patients with bilateral vestibular hypofunction (BVH) often suffer from imbalance, gait problems, and oscillopsia. Noisy galvanic vestibular stimulation (GVS), a technique that non-invasively stimulates the vestibular afferents, has been shown to enhance postural and walking stability. However, no study has investigated how it affects stability and neural activities while standing and walking with a 2 Hz head yaw turning. Herein, we investigated this issue by comparing differences in neural activities during standing and walking with a 2 Hz head turning, before and after noisy GVS. We applied zero-mean gaussian white noise signal stimulations in the mastoid processes of 10 healthy individuals and seven patients with BVH, and simultaneously recorded electroencephalography (EEG) signals with 32 channels. We analyzed the root mean square (RMS) of the center of pressure (COP) sway during 30 s of standing, utilizing AMTI force plates (Advanced Mechanical Technology Inc., Watertown, MA, USA). Head rotation quality when walking with a 2 Hz head yaw, with and without GVS, was analyzed using a VICON system (Vicon Motion Systems Ltd., Oxford, UK) to evaluate GVS effects on static and dynamic postural control. The RMS of COP sway was significantly reduced during GVS while standing, for both patients and healthy subjects. During walking, 2 Hz head yaw movements was significantly improved by noisy GVS in both groups. Accordingly, the EEG power of theta, alpha, beta, and gamma bands significantly increased in the left parietal lobe after noisy GVS during walking and standing in both groups. GVS post-stimulation effect changed EEG activities in the left and right precentral gyrus, and the right parietal lobe. After stimulation, EEG activity changes were greater in healthy subjects than in patients. Our findings reveal noisy GVS as a non-invasive therapeutic alternative to improve postural stability in patients with BVH. This novel approach provides insight to clinicians and researchers on brain activities during noisy GVS in standing and walking conditions in both healthy and BVH patients.

13.
Front Neurol ; 11: 485, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32595589

RESUMO

To evaluate vestibular function in the clinic, current assessments are applied under static conditions, such as with the subject in a sitting or supine position. Considering the complexities of daily activities, the combination of dynamic activities, dynamic visual acuity (DVA) and postural control could produce an evaluation that better reflects vestibular function in daily activities. Objective: To develop a novel sensor-based system to investigate DVA, walking trajectory, head and trunk movements and the chest-pelvis rotation ratio during forward and backward overground walking in both healthy individuals and patients with vestibular hypofunction. Methods: Fifteen healthy subjects and 7 patients with bilateral vestibular hypofunction (BVH) were recruited for this study. Inertial measurement units were placed on each subject's head and torso. Each subject walked forward and backward for 5 m twice with 2 Hz head yaw. Our experiment comprised 2 stages. In stage 1, we measured forward (FW), backward (BW), and medial-lateral (MLW) walking trajectories; head and trunk movements; and the chest-pelvis rotation ratio. In stage 2, we measured standing and locomotion DVA (loDVA). Using Mann-Whitney U-test, we compared the abovementioned parameters between the 2 groups. Results: Patients exhibited an in-phase chest/pelvis reciprocal rotation ratio only in FW. The walking trajectory deviation, calculated by normalizing the summation of medial-lateral swaying with 1/2 body height (%), was significantly larger (FW mean ± standard deviation: 20.4 ± 7.1% (median (M)/interquartile range (IQR): 19.3/14.4-25.2)in healthy vs. 43.9 ± 27. 3% (M/IQR: 36.9/21.3-56.9) in patients, p = 0.020)/(BW mean ± standard deviation: 19.2 ± 11.5% (M/IQR: 13.6/10.4-25.3) in healthy vs. 29.3 ± 6.4% (M/IQR: 27.7/26.5-34.4) in patients, p = 0.026), and the walking DVA was also significantly higher (LogMAR score in the patient group [FW LogMAR: rightDVA: mean ± standard deviation:0.127 ± 0.081 (M/IQR: 0.127/0.036-0.159) in healthy vs. 0.243 ± 0.101 (M/IQR: 0.247/0.143-0.337) in patients (p = 0.013) and leftDVA: 0.136 ± 0.096 (M/IQR: 0.127/0.036-0.176) in healthy vs. 0.258 ± 0.092 (M/IQR: 0.247/0.176-0.301) in patients (p = 0.016); BW LogMAR: rightDVA: mean ± standard deviation: 0.162 ± 0.097 (M/IQR: 0.159/0.097-0.273) in healthy vs. 0.281 ± 0.130 (M/IQR: 0.273/0.176-0.418) in patients(p = 0.047) and leftDVA: 0.156 ± 0.101 (M/IQR: 0.159/0.097-0.198) in healthy vs. 0.298 ± 0.153 (M/IQR: 0.2730/0.159-0.484) in patients (p = 0.038)]. Conclusions: Our sensor-based vestibular evaluation system provided a more functionally relevant assessment for the identification of BVH patients.

14.
J Chin Med Assoc ; 83(10): 898-899, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32520771

RESUMO

Artificial intelligence (AI) has been widely applied in the medical field and achieved enormous milestones in helping specialists to make diagnosis and remedy decisions, particularly in the field of eye diseases and ophthalmic screening. With the development of AI-based systems, the enormous hardware and software resources are required for optimal performance. In reality, there are many places on the planet where such resources are highly limited. Hence, the smartphone-based AI systems can be used to provide a remote control route to quickly screen eye diseases such as diabetic-related retinopathy or diabetic macular edema. However, the performance of such mobile-based AI systems is still uncharted territory. In this article, we discuss the issues of computing resource consumption and performance of the mobile device-based AI systems and highlight recent research on the feasibility and future potential of application of the mobile device-based AI systems in telemedicine.

15.
J Chin Med Assoc ; 83(11): 981-983, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32568967

RESUMO

Artificial intelligence (AI), Internet of Things (IoT), and telemedicine are deeply involved in our daily life and have also been extensively applied in the medical field, especially in ophthalmology. Clinical ophthalmologists are required to perform a vast array of image exams and analyze images containing complicated information, which allows them to diagnose the disease type and grade, make a decision on remedy, and predict treatment outcomes. AI has a great potential to assist ophthalmologists in their daily routine of image analysis and relieve their work burden. However, in spite of these prospects, the application of AI may also be controversial and associated with several legal, ethical, and sociological concerns. In spite of these issues, AI has indeed become an irresistible trend and is widely used by medical specialists in their daily routines in what we can call now, the era of AI. This review will encompass those issues and focus on recent research on the AI application in ophthalmology and telemedicine.

16.
J Chin Med Assoc ; 83(11): 1034-1038, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32452907

RESUMO

BACKGROUND: Optical coherence tomography (OCT) is considered as a sensitive and noninvasive tool to evaluate the macular lesions. In patients with diabetes mellitus (DM), the existence of diabetic macular edema (DME) can cause significant vision impairment and further intravitreal injection (IVI) of anti-vascular endothelial growth factor (VEGF) is needed. However, the increasing number of DM patients makes it a big burden for clinicians to manually determine whether DME exists in the OCT images. The artificial intelligence (AI) now enormously applied to many medical territories may help reduce the burden on clinicians. METHODS: We selected DME patients receiving IVI of anti-VEGF or corticosteroid at Taipei Veterans General Hospital in 2017. All macular cross-sectional scan OCT images were collected retrospectively from the eyes of these patients from January 2008 to July 2018. We further established AI models based on convolutional neural network architecture to determine whether the DM patients have DME by OCT images. RESULTS: Based on the convolutional neural networks, InceptionV3 and VGG16, our AI system achieved a high DME diagnostic accuracy of 93.09% and 92.82%, respectively. The sensitivity of the VGG16 and InceptionV3 models was 96.48% and 95.15%., respectively. The specificity was corresponding to 86.67% and 89.63% for VGG16 and InceptionV3, respectively. We further developed an OCT-driven platform based on these AI models. CONCLUSION: We successfully set up AI models to provide an accurate diagnosis of DME by OCT images. These models may assist clinicians in screening DME in DM patients in the future.

18.
J Chin Med Assoc ; 82(4): 328-334, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30946211

RESUMO

BACKGROUND: The technology of using inertial measurement units (IMUs) to detect motions in different body segments has drawn enormous attention to research and industry. In our previous research, we have applied IMUs in evaluating and treating patients with vestibular hypofunction. Furthermore, according to the research, when a person's head rotates over 60° on either side in the horizontal plane, and desires to focus vision on any targets, then the function of gaze shift comes in to operation. Herein, we aimed to use IMUs to build up a system to evaluate vestibular ocular reflex (VOR) during gaze shifting maneuver. METHODS: In this study, we developed a platform, which combines the features of gaze shift and computerized dynamic visual acuity (cDVA), called the gaze shift DVA (gsDVA) platform. The gsDVA platform measures the orientations of the subject's head by IMU, and executed the evaluation according to the algorithm that was developed by us. Finally, we used the VICON system to validate the performance of gsDVA platform. RESULTS: The performance of the accuracy was 2.41° ± 1.08°, the maximal sensor error was within 4.25°, and highly correlated between our platform and VICON (p < 0.05, R = 0.99). The intraclass correlation coefficient (ICC) of between-day and within-day was 0.984 and 0.999, respectively. Furthermore, the platform not only executed the evaluation automatically but also recorded other information besides the head orientation, such as rotation speed, rotation time, reaction time, and visual acuity. CONCLUSION: In this study, we demonstrated the utility of vestibular evaluation, and this platform can help to clarify the relationship between gaze shift and VOR. This methodology is useful and can be applied efficiently to different disease groups for interactive evaluation and rehabilitation programs.


Assuntos
Reflexo Vestíbulo-Ocular/fisiologia , Movimentos da Cabeça/fisiologia , Humanos , Tempo de Reação , Rotação , Doenças Vestibulares/fisiopatologia , Acuidade Visual
19.
Theranostics ; 9(1): 232-245, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30662564

RESUMO

Artificial intelligence (AI) based on convolutional neural networks (CNNs) has a great potential to enhance medical workflow and improve health care quality. Of particular interest is practical implementation of such AI-based software as a cloud-based tool aimed for telemedicine, the practice of providing medical care from a distance using electronic interfaces. Methods: In this study, we used a dataset of labeled 35,900 optical coherence tomography (OCT) images obtained from age-related macular degeneration (AMD) patients and used them to train three types of CNNs to perform AMD diagnosis. Results: Here, we present an AI- and cloud-based telemedicine interaction tool for diagnosis and proposed treatment of AMD. Through deep learning process based on the analysis of preprocessed optical coherence tomography (OCT) imaging data, our AI-based system achieved the same image discrimination rate as that of retinal specialists in our hospital. The AI platform's detection accuracy was generally higher than 90% and was significantly superior (p < 0.001) to that of medical students (69.4% and 68.9%) and equal (p = 0.99) to that of retinal specialists (92.73% and 91.90%). Furthermore, it provided appropriate treatment recommendations comparable to those of retinal specialists. Conclusions: We therefore developed a website for realistic cloud computing based on this AI platform, available at https://www.ym.edu.tw/~AI-OCT/. Patients can upload their OCT images to the website to verify whether they have AMD and require treatment. Using an AI-based cloud service represents a real solution for medical imaging diagnostics and telemedicine.


Assuntos
Inteligência Artificial , Tomada de Decisões , Testes Diagnósticos de Rotina/métodos , Processamento de Imagem Assistida por Computador/métodos , Degeneração Macular/diagnóstico , Tomografia de Coerência Óptica/métodos , Humanos , Software , Telemedicina/métodos
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