The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Howard L Weiner - One of the best experts on this subject based on the ideXlab platform.
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evaluation of an Online Platform for multiple sclerosis research patient description validation of severity scale and exploration of bmi effects on disease course
PLOS ONE, 2013Co-Authors: Riley Bove, Elizabeth Secor, Brian C Healy, Alexander Musallam, Timothy E Vaughan, Bonnie I Glanz, Emily Greeke, Howard L WeinerAbstract:Objectives: To assess the potential of an Online Platform, PatientsLikeMe.com (PLM), for research in multiple sclerosis (MS). An investigation of the role of body mass index (BMI) on MS disease course was conducted to illustrate the utility of the Platform. Methods: First, we compared the demographic characteristics of subjects from PLM and from a regional MS center. Second, we validated PLM’s patient-reported outcome measure (MS Rating Scale, MSRS) against standard physician-rated tools. Finally, we analyzed the relation of BMI to the MSRS measure. Results: Compared with 4,039 MS Center patients, the 10,255 PLM members were younger, more educated, and less often male and white. Disease course was more often relapsing remitting, with younger symptom onset and shorter disease duration. Differences were significant because of large sample sizes but small in absolute terms. MSRS scores for 121 MS Center patients revealed acceptable agreement between patient-derived and physician-derived composite scores (weighted kappa=0.46). The Walking domain showed the highest weighted kappa (0.73) and correlation (rs=0.86) between patient and physician scores. Additionally, there were good correlations between the patient-reported MSRS composite and walking scores and physician-derived measures: Expanded Disability Status Scale (composite rs=0.61, walking rs=0.74), Timed 25 Foot Walk (composite rs=0.70, walking rs=0.69), and Ambulation Index (composite rs=0.81, walking rs=0.84). Finally, using PLM data, we found a modest correlation between BMI and cross-sectional MSRS (rho=0.17) and no association between BMI and disease course. Conclusions: The PLM population is comparable to a clinic population, and its patient-reported MSRS is correlated with existing clinical instruments. Thus, this Online Platform may provide a venue for MS investigations with unique strengths (frequent data collection, large sample sizes). To illustrate its applicability, we assessed the role of BMI in MS disease course but did not find a clinically meaningful role for BMI in this setting.
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evaluation of an Online Platform for multiple sclerosis research patient description validation of severity scale and exploration of bmi effects on disease course
PLOS ONE, 2013Co-Authors: Riley Bove, Elizabeth Secor, Brian C Healy, Alexander Musallam, Timothy E Vaughan, Bonnie I Glanz, Emily Greeke, Howard L WeinerAbstract:Objectives: To assess the potential of an Online Platform, PatientsLikeMe.com (PLM), for research in multiple sclerosis (MS). An investigation of the role of body mass index (BMI) on MS disease course was conducted to illustrate the utility of the Platform. Methods: First, we compared the demographic characteristics of subjects from PLM and from a regional MS center. Second, we validated PLM’s patient-reported outcome measure (MS Rating Scale, MSRS) against standard physician-rated tools. Finally, we analyzed the relation of BMI to the MSRS measure. Results: Compared with 4,039 MS Center patients, the 10,255 PLM members were younger, more educated, and less often male and white. Disease course was more often relapsing remitting, with younger symptom onset and shorter disease duration. Differences were significant because of large sample sizes but small in absolute terms. MSRS scores for 121 MS Center patients revealed acceptable agreement between patient-derived and physician-derived composite scores (weighted kappa=0.46). The Walking domain showed the highest weighted kappa (0.73) and correlation (rs=0.86) between patient and physician scores. Additionally, there were good correlations between the patient-reported MSRS composite and walking scores and physician-derived measures: Expanded Disability Status Scale (composite rs=0.61, walking rs=0.74), Timed 25 Foot Walk (composite rs=0.70, walking rs=0.69), and Ambulation Index (composite rs=0.81, walking rs=0.84). Finally, using PLM data, we found a modest correlation between BMI and cross-sectional MSRS (rho=0.17) and no association between BMI and disease course. Conclusions: The PLM population is comparable to a clinic population, and its patient-reported MSRS is correlated with existing clinical instruments. Thus, this Online Platform may provide a venue for MS investigations with unique strengths (frequent data collection, large sample sizes). To illustrate its applicability, we assessed the role of BMI in MS disease course but did not find a clinically meaningful role for BMI in this setting.
Jan Egger - One of the best experts on this subject based on the ideXlab platform.
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an Online Platform for automatic skull defect restoration and cranial implant design
Medical Imaging 2021: Image-Guided Procedures Robotic Interventions and Modeling, 2021Co-Authors: Antonio Pepe, Christina Gsaxner, Jan EggerAbstract:We introduce a fully automatic system for cranial implant design, a common task in cranioplasty operations. The system is currently integrated in Studierfenster (http://studierfenster.tugraz.at/), an Online, cloud-based medical image processing Platform for medical imaging applications. Enhanced by deep learning algorithms, the system automatically restores the missing part of a skull (i.e., skull shape completion) and generates the desired implant by subtracting the defective skull from the completed skull. The generated implant can be downloaded in the STereoLithography (.stl) format directly via the browser interface of the system. The implant model can then be sent to a 3D printer for in loco implant manufacturing. Furthermore, thanks to the standard format, the user can thereafter load the model into another application for post-processing whenever necessary. Such an automatic cranial implant design system can be integrated into the clinical practice to improve the current routine for surgeries related to skull defect repair (e.g., cranioplasty). Our system, although currently intended for educational and research use only, can be seen as an application of additive manufacturing for fast, patient-specific implant design.
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an Online Platform for automatic skull defect restoration and cranial implant design
arXiv: Medical Physics, 2020Co-Authors: Antonio Pepe, Christina Gsaxner, Jan EggerAbstract:We introduce a fully automatic system for cranial implant design, a common task in cranioplasty operations. The system is currently integrated in Studierfenster (this http URL), an Online, cloud-based medical image processing Platform for medical imaging applications. Enhanced by deep learning algorithms, the system automatically restores the missing part of a skull (i.e., skull shape completion) and generates the desired implant by subtracting the defective skull from the completed skull. The generated implant can be downloaded in the STereoLithography (.stl) format directly via the browser interface of the system. The implant model can then be sent to a 3D printer for in loco implant manufacturing. Furthermore, thanks to the standard format, the user can thereafter load the model into another application for post-processing whenever necessary. Such an automatic cranial implant design system can be integrated into the clinical practice to improve the current routine for surgeries related to skull defect repair (e.g., cranioplasty). Our system, although currently intended for educational and research use only, can be seen as an application of additive manufacturing for fast, patient-specific implant design.
Riley Bove - One of the best experts on this subject based on the ideXlab platform.
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evaluation of an Online Platform for multiple sclerosis research patient description validation of severity scale and exploration of bmi effects on disease course
PLOS ONE, 2013Co-Authors: Riley Bove, Elizabeth Secor, Brian C Healy, Alexander Musallam, Timothy E Vaughan, Bonnie I Glanz, Emily Greeke, Howard L WeinerAbstract:Objectives: To assess the potential of an Online Platform, PatientsLikeMe.com (PLM), for research in multiple sclerosis (MS). An investigation of the role of body mass index (BMI) on MS disease course was conducted to illustrate the utility of the Platform. Methods: First, we compared the demographic characteristics of subjects from PLM and from a regional MS center. Second, we validated PLM’s patient-reported outcome measure (MS Rating Scale, MSRS) against standard physician-rated tools. Finally, we analyzed the relation of BMI to the MSRS measure. Results: Compared with 4,039 MS Center patients, the 10,255 PLM members were younger, more educated, and less often male and white. Disease course was more often relapsing remitting, with younger symptom onset and shorter disease duration. Differences were significant because of large sample sizes but small in absolute terms. MSRS scores for 121 MS Center patients revealed acceptable agreement between patient-derived and physician-derived composite scores (weighted kappa=0.46). The Walking domain showed the highest weighted kappa (0.73) and correlation (rs=0.86) between patient and physician scores. Additionally, there were good correlations between the patient-reported MSRS composite and walking scores and physician-derived measures: Expanded Disability Status Scale (composite rs=0.61, walking rs=0.74), Timed 25 Foot Walk (composite rs=0.70, walking rs=0.69), and Ambulation Index (composite rs=0.81, walking rs=0.84). Finally, using PLM data, we found a modest correlation between BMI and cross-sectional MSRS (rho=0.17) and no association between BMI and disease course. Conclusions: The PLM population is comparable to a clinic population, and its patient-reported MSRS is correlated with existing clinical instruments. Thus, this Online Platform may provide a venue for MS investigations with unique strengths (frequent data collection, large sample sizes). To illustrate its applicability, we assessed the role of BMI in MS disease course but did not find a clinically meaningful role for BMI in this setting.
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evaluation of an Online Platform for multiple sclerosis research patient description validation of severity scale and exploration of bmi effects on disease course
PLOS ONE, 2013Co-Authors: Riley Bove, Elizabeth Secor, Brian C Healy, Alexander Musallam, Timothy E Vaughan, Bonnie I Glanz, Emily Greeke, Howard L WeinerAbstract:Objectives: To assess the potential of an Online Platform, PatientsLikeMe.com (PLM), for research in multiple sclerosis (MS). An investigation of the role of body mass index (BMI) on MS disease course was conducted to illustrate the utility of the Platform. Methods: First, we compared the demographic characteristics of subjects from PLM and from a regional MS center. Second, we validated PLM’s patient-reported outcome measure (MS Rating Scale, MSRS) against standard physician-rated tools. Finally, we analyzed the relation of BMI to the MSRS measure. Results: Compared with 4,039 MS Center patients, the 10,255 PLM members were younger, more educated, and less often male and white. Disease course was more often relapsing remitting, with younger symptom onset and shorter disease duration. Differences were significant because of large sample sizes but small in absolute terms. MSRS scores for 121 MS Center patients revealed acceptable agreement between patient-derived and physician-derived composite scores (weighted kappa=0.46). The Walking domain showed the highest weighted kappa (0.73) and correlation (rs=0.86) between patient and physician scores. Additionally, there were good correlations between the patient-reported MSRS composite and walking scores and physician-derived measures: Expanded Disability Status Scale (composite rs=0.61, walking rs=0.74), Timed 25 Foot Walk (composite rs=0.70, walking rs=0.69), and Ambulation Index (composite rs=0.81, walking rs=0.84). Finally, using PLM data, we found a modest correlation between BMI and cross-sectional MSRS (rho=0.17) and no association between BMI and disease course. Conclusions: The PLM population is comparable to a clinic population, and its patient-reported MSRS is correlated with existing clinical instruments. Thus, this Online Platform may provide a venue for MS investigations with unique strengths (frequent data collection, large sample sizes). To illustrate its applicability, we assessed the role of BMI in MS disease course but did not find a clinically meaningful role for BMI in this setting.
Antonio Pepe - One of the best experts on this subject based on the ideXlab platform.
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an Online Platform for automatic skull defect restoration and cranial implant design
Medical Imaging 2021: Image-Guided Procedures Robotic Interventions and Modeling, 2021Co-Authors: Antonio Pepe, Christina Gsaxner, Jan EggerAbstract:We introduce a fully automatic system for cranial implant design, a common task in cranioplasty operations. The system is currently integrated in Studierfenster (http://studierfenster.tugraz.at/), an Online, cloud-based medical image processing Platform for medical imaging applications. Enhanced by deep learning algorithms, the system automatically restores the missing part of a skull (i.e., skull shape completion) and generates the desired implant by subtracting the defective skull from the completed skull. The generated implant can be downloaded in the STereoLithography (.stl) format directly via the browser interface of the system. The implant model can then be sent to a 3D printer for in loco implant manufacturing. Furthermore, thanks to the standard format, the user can thereafter load the model into another application for post-processing whenever necessary. Such an automatic cranial implant design system can be integrated into the clinical practice to improve the current routine for surgeries related to skull defect repair (e.g., cranioplasty). Our system, although currently intended for educational and research use only, can be seen as an application of additive manufacturing for fast, patient-specific implant design.
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an Online Platform for automatic skull defect restoration and cranial implant design
arXiv: Medical Physics, 2020Co-Authors: Antonio Pepe, Christina Gsaxner, Jan EggerAbstract:We introduce a fully automatic system for cranial implant design, a common task in cranioplasty operations. The system is currently integrated in Studierfenster (this http URL), an Online, cloud-based medical image processing Platform for medical imaging applications. Enhanced by deep learning algorithms, the system automatically restores the missing part of a skull (i.e., skull shape completion) and generates the desired implant by subtracting the defective skull from the completed skull. The generated implant can be downloaded in the STereoLithography (.stl) format directly via the browser interface of the system. The implant model can then be sent to a 3D printer for in loco implant manufacturing. Furthermore, thanks to the standard format, the user can thereafter load the model into another application for post-processing whenever necessary. Such an automatic cranial implant design system can be integrated into the clinical practice to improve the current routine for surgeries related to skull defect repair (e.g., cranioplasty). Our system, although currently intended for educational and research use only, can be seen as an application of additive manufacturing for fast, patient-specific implant design.
Felipe Vial - One of the best experts on this subject based on the ideXlab platform.
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bacav a new free Online Platform for clinical back averaging
Clinical Neurophysiology Practice, 2020Co-Authors: Felipe Vial, Patrick Mcgurrin, Sanaz Attaripour, Mark HallettAbstract:Abstract Objective The back-average technique is very useful to study the relation between the activity in the cortex and the muscles. It has two main clinical applications, Bereitschaftspotential (BP) recording and myoclonus studies. The BP is a slow wave negativity originating in the supplementary motor cortex and premotor cortex that precedes voluntary movements. This wave also precedes involuntary movements in functional movement disorders (FMD), and it can be used as a helpful diagnostic tool. For the myoclonus studies, the back-average technique is very important to help localizing the source of the myoclonus. The hardware needed to do BP or myoclonus studies is standard and available in any electrophysiology lab, but there are not many software solutions to do the analysis. In this article together with describing the methodology that we use for recording clinical BPs and myoclonus, we present BacAv, an Online free application that we developed for the purpose of doing back-average analysis. Methods BacAv was developed in “R” language using Rstudio, a free integrated development environment. The recommended parameters for the data acquisition for BP recording and myoclonus studies are given in this section. Results The Platform was successfully developed, is able to read txt files, look for muscle bursts, segment the data, and plot the average. The parameters of the algorithm that look for the muscle bursts can be adapted according to the characteristics of the dataset. Conclusion We have developed software for clinicians who do not have sophisticated equipment to do back-averaging. Significance This tool will make this useful analysis method more available in a clinical environment.
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tremoroton a new free Online Platform for tremor analysis
Clinical Neurophysiology Practice, 2020Co-Authors: Felipe Vial, Patrick Mcgurrin, Thomas Osterholt, Debra Ehrlich, Dietrich Haubenberger, Mark HallettAbstract:Abstract Objective The electrophysiological classification of tremors can be a key element in the diagnosis and can facilitate treatment of a patient with tremor; however, the ability to conduct electrophysiological studies of tremor is not widely available. The purpose of this study was to develop and validate a free Online Platform for tremor analysis. Methods An Online Platform for tremor analysis was developed using “R” language; called “Tremoroton”. For validation, we compared the frequency estimation of the tremor obtained with Tremoroton compared with a commercially available software in a cohort of 20 patients (10 with essential tremor and 10 with Parkinson diagnosis), comparing the activity recorded on the accelerometer, extensor carpi radialis and flexor carpi radialis EMG. An intraclass correlation coefficient was used for the comparison. Results The final version of tremoroton is now Online. It allows reading up to 6 channels, and will do time, frequency, time-frequency analysis and calculate coherence. We demonstrated a high correlation in frequency measurements (0.97 (0.945–0.984, 95% IC) for the accelerometers, 0.98 (0.977–0.994, 95% IC) for the extensor carpi radialis EMG, and 0.99 (0.987–0.997, 95% IC) for the flexor carpi radialis EMG) when compared to a commercial software. Conclusion We were able to develop and validate a free Online Platform for tremor analysis. Significance Making this tool available should help expanding tremor analysis techniques from research to the clinical setting.
