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https://www.readbyqxmd.com/read/28227990/using-computational-phantoms-to-improve-delivery-of-tumor-treating-fields-ttfields-to-patients
#1
Ze'ev Bomzon, Hadas Sara Hershkovich, Noa Urman, Aafia Chaudhry, Dario Garcia-Carracedo, Anders R Korshoej, Uri Weinberg, Cornelia Wenger, Pedro Miranda, Yoram Wasserman, Eilon D Kirson, Yoram, Ze'ev Bomzon, Hadas Sara Hershkovich, Noa Urman, Aafia Chaudhry, Dario Garcia-Carracedo, Anders R Korshoej, Uri Weinberg, Cornelia Wenger, Pedro Miranda, Yoram Wasserman, Eilon D Kirson, Yoram, Uri Weinberg, Cornelia Wenger, Noa Urman, Hadas Sara Hershkovich, Yoram Wasserman, Anders R Korshoej, Eilon D Kirson, Dario Garcia-Carracedo, Pedro Miranda, Aafia Chaudhry, Zeev Bomzon, Yoram
This paper reviews the state-of-the-art in simulation-based studies of Tumor Treating Fields (TTFields) and highlights major aspects of TTFields in which simulation-based studies could affect clinical outcomes. A major challenge is how to simulate multiple scenarios rapidly for TTFields delivery. Overcoming this challenge will enable a better understanding of how TTFields distribution is correlated with disease progression, leading to better transducer array designs and field optimization procedures, ultimately improving patient outcomes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227970/combining-a-hybrid-robotic-system-with-a-bain-machine-interface-for-the-rehabilitation-of-reaching-movements-a-case-study-with-a-stroke-patient
#2
F Resquin, J Ibanez, J Gonzalez-Vargas, F Brunetti, I Dimbwadyo, S Alves, L Carrasco, L Torres, Jose Luis Pons, F Resquin, J Ibañez, J Gonzalez-Vargas, F Brunetti, I Dimbwadyo, S Alves, L Carrasco, L Torres, Jose Luis Pons, S Alves, Jose Luis Pons, F Brunetti, J Gonzalez-Vargas, F Resquin, I Dimbwadyo, L Carrasco, L Torres, J Ibanez
Reaching and grasping are two of the most affected functions after stroke. Hybrid rehabilitation systems combining Functional Electrical Stimulation with Robotic devices have been proposed in the literature to improve rehabilitation outcomes. In this work, we present the combined use of a hybrid robotic system with an EEG-based Brain-Machine Interface to detect the user's movement intentions to trigger the assistance. The platform has been tested in a single session with a stroke patient. The results show how the patient could successfully interact with the BMI and command the assistance of the hybrid system with low latencies...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227782/predicting-short-term-icu-outcomes-using-a-sequential-contrast-motif-based-classification-framework
#3
Shameek Ghosh, Hung Nguyen, Jinyan Li, Shameek Ghosh, Hung Nguyen, Jinyan Li, Shameek Ghosh, Hung Nguyen, Jinyan Li
Critical ICU events like acute hypotension and septic shock are dangerous complications, leading to multiple organ failures and eventual death. Previously, pattern mining algorithms have been employed for extracting interesting rules in various clinical domains. However, the extracted rules are directly investigated by clinicians for diagnosing a disease. Towards this purpose, there is a need to develop advanced prediction models which integrate dynamic patterns to learn a patient's physiological condition...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227763/network-effects-and-pathways-in-deep-brain-stimulation-in-parkinson-s-disease
#4
N Koirala, V Fleischer, O Granert, G Deuschl, M Muthuraman, S Groppa, N Koirala, V Fleischer, O Granert, G Deuschl, M Muthuraman, S Groppa
Deep brain stimulation of subthalamic nucleus (STN-DBS) became a standard therapeutic option in Parkinson's disease (PD), even though the underlying modulated network of STN-DBS is still poorly described. Probabilistic tractography and connectivity analysis as derived from diffusion tensor imaging (DTI) were performed together with modelling of implanted electrode positions and linked postoperative clinical outcome. Fifteen patients with idiopathic PD without dementia were selected for DBS treatment. After pre-processing, probabilistic tractography was run from cortical and subcortical seeds of the hypothesized network to targets represented by the positions of the active DBS contacts...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227698/predicting-brain-stimulation-treatment-outcomes-of-depressed-patients-through-the-classification-of-eeg-oscillations
#5
Alaa M Al-Kaysi, Ahmed Al-Ani, Colleen K Loo, Michael Breakspear, Tjeerd W Boonstra, Alaa M Al-Kaysi, Ahmed Al-Ani, Colleen K Loo, Michael Breakspear, Tjeerd W Boonstra, Michael Breakspear, Ahmed Al-Ani, Tjeerd W Boonstra, Colleen K Loo
Major depressive disorder (MDD) is a mental disorder that is characterized by negative thoughts, mood and behavior. Transcranial direct current stimulation (tDCS) has recently emerged as a promising brain-stimulation treatment for MDD. A standard tDCS treatment involves numerous sessions that run over a few weeks, however, not all participants respond to this type of treatment. This study aims to predict which patients improve in mood and cognition in response to tDCS treatment by analyzing electroencephalography (EEG) of MDD patients that was collected at the start of tDCS treatment...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227691/understanding-the-cochlear-implant-environment-by-mapping-perilymph-proteomes-from-different-species
#6
Jonathan C Palmer, Megan S Lord, Jeremy L Pinyon, Andrew K Wise, Nigel H Lovell, Paul M Carter, Ya Lang Enke, Gary D Housley, Rylie A Green, Jonathan C Palmer, Megan S Lord, Jeremy L Pinyon, Andrew K Wise, Nigel H Lovell, Paul M Carter, Ya Lang Enke, Gary D Housley, Rylie A Green, Ya Lang Enke, Rylie A Green, Jonathan C Palmer, Nigel H Lovell, Paul M Carter, Jeremy L Pinyon, Gary D Housley, Andrew K Wise, Megan S Lord
Cochlear implants operate within a bony channel of the cochlea, bathed in a fluid known as the perilymph. The perilymph is a complex fluid containing ions and proteins, which are known to actively interact with metallic electrodes. To improve our understanding of how cochlear implant performance varies in preclinical in vivo studies in comparison to human trials and patient outcomes, the protein composition (or perilymph proteome) is needed. Samples of perilymph were gathered from feline and guinea pig subjects and analyzed using liquid chromatography with tandem mass spectrometry (LC-MS/MS) to produce proteomes and compare against the recently published human proteome...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227624/relationship-between-gait-variables-and-domains-of-neurologic-dysfunction-in-multiple-sclerosis-using-six-minute-walk-test
#7
Asma Qureshi, Maite Brandt-Pearce, Myla D Goldman, Asma Qureshi, Maite Brandt-Pearce, Myla D Goldman, Asma Qureshi, Myla D Goldman, Maite Brandt-Pearce
Most multiple sclerosis (MS) patients eventually suffer from mobility impairment, and thus it is critical that walking disability in MS be accurately assessed. The six-minute walk test (6MWT), a reliable MS measure, is traditionally used to determine the distance covered in six minutes using a standard protocol. With the availability of body sensor networks (BSNs), researchers are interested in leveraging BSN data for finding new gait assessment anchors for improved separability performance. Further, current methods for gait assessments are insufficient since assessments are absolute, performed by comparing outcomes to the statistical norms established from diverse patient data despite natural inter-patient variability...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227555/eeg-patterns-of-subacute-stroke-patients-performing-motor-tasks-correlate-with-motor-functional-outcome-preliminary-results
#8
Wanjoo Park, Yun-Hee Kim, Sung-Phil Kim, Laehyun Kim, Wanjoo Park, Yun-Hee Kim, Sung-Phil Kim, Laehyun Kim, Yun-Hee Kim, Sung-Phil Kim, Wanjoo Park, Laehyun Kim
If an early predictor of motor functional outcome after stroke were available, stroke patients would receive more appropriate treatments for motor recovery. We performed a correlation analysis of the electroencephalography (EEG) signal patterns of nine subacute stroke patients (recorded 22.9 ± 7.1 days after onset) and their motor recovery rates (measured 100.2 ± 8.9 days after onset). The beta band spectral power in the bilateral motor cortex after physical upper limb movement correlated significantly with the motor recovery rates [Fugl-Meyer assessment (FMA) scores; Pearson's linear correlation, p <; 0...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227492/biomems-based-coding-for-secure-medical-diagnostic-devices
#9
Tuan Le, Gabriel Salles-Loustau, Laleh Najafizadeh, Mehdi Javanmard, Saman Zonouz, Tuan Le, Gabriel Salles-Loustau, Laleh Najafizadeh, Mehdi Javanmard, Saman Zonouz, Saman Zonouz, Gabriel Salles-Loustau, Laleh Najafizadeh, Tuan Le, Mehdi Javanmard
Trustworthy and usable point-of-care solutions require not only effective disease diagnostic procedures to ensure delivery of rapid and accurate outcomes, but also lightweight privacy-preserving capabilities. In this paper, we present a Biomedical Microelectromachanical System (BioMEMS)-based sensor for portable, inexpensive smartphone-based biomarker detection. The biosensor presented here provides the ability for signal encryption at the physical sensor level to ensure patient's diagnostic confidentiality...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227468/patient-emulator-a-tool-for-testing-mechanical-ventilation-therapies
#10
Nikolaos Karamolegkos, Antonio Albanese, Fernando Isaza, Nicolas W Chbat, Nikolaos Karamolegkos, Antonio Albanese, Fernando Isaza, Nicolas W Chbat, Nikolaos Karamolegkos, Antonio Albanese, Nicolas W Chbat, Fernando Isaza
Several modes of mechanical ventilation are clinically available. The differences among them in terms of efficacy and patient outcomes are not clear yet. Testing and comparison of mechanical ventilation modes via human or animal trials is a very challenging and costly process. In this paper, we present the patient emulator (PE), a novel system that can be used as a platform for in-silico testing of mechanical ventilation therapies. The system is based on a large-scale integrated mathematical model of the human cardiopulmonary system interfaced with a physical ventilator via a controlled piston-cylinder actuator...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227337/prediction-of-the-outcome-in-cardiac-arrest-patients-undergoing-hypothermia-using-eeg-wavelet-entropy
#11
Hana Moshirvaziri, Nima Ramezan-Arab, Shadnaz Asgari, Hana Moshirvaziri, Nima Ramezan-Arab, Shadnaz Asgari, Hana Moshirvaziri, Nima Ramezan-Arab, Shadnaz Asgari
Cardiac arrest (CA) is the leading cause of death in the United States. Induction of hypothermia has been found to improve the functional recovery of CA patients after resuscitation. However, there is no clear guideline for the clinicians yet to determine the prognosis of the CA when patients are treated with hypothermia. The present work aimed at the development of a prognostic marker for the CA patients undergoing hypothermia. A quantitative measure of the complexity of Electroencephalogram (EEG) signals, called wavelet sub-band entropy, was employed to predict the patients' outcomes...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227220/selection-of-an-optimal-feature-set-to-predict-heart-transplantation-outcomes
#12
Dennis Medved, Pierre Nugues, Johan Nilsson, Dennis Medved, Pierre Nugues, Johan Nilsson, Dennis Medved, Johan Nilsson, Pierre Nugues
Heart transplantation (HT) is a life saving procedure, but a limited donor supply forces the surgeons to prioritize the recipients. The understanding of factors that predict mortality could help the doctors with this task. The objective of this study is to find locally optimal feature sets to predict survival of HT patients for different time periods. To this end, we applied logistic regression together with a greedy forward and backward search. As data source, we used the United Network for Organ Sharing (UNOS) registry, where we extracted adult patients (>17 years) from January 1997 to December 2008...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227181/co-activation-of-saphenous-nerve-fibers-a-potential-therapeutic-mechanism-of-percutaneous-tibial-nerve-stimulation
#13
Christopher W Elder, Paul B Yoo, Christopher W Elder, Paul B Yoo, Paul B Yoo, Christopher W Elder
Percutaneous tibial nerve stimulation (PTNS) is a minimally invasive and effective treatment for overactive bladder (OAB). However, clinical trials show that positive therapeutic outcomes among patients are difficult to predict (failure rate = 35% to 50%). Inconsistencies in the stimulation amplitudes used clinically and those used in preclinical animal studies led us to hypothesize that OAB therapy involves a secondary bladder-inhibitory pathway. In this paper, we implemented and tested a computer model of the human lower leg that investigated the differential activation of the saphenous nerve (SAFN) and tibial nerve (TN) during percutaneous electrical stimulation...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227144/optimal-medication-dosing-from-suboptimal-clinical-examples-a-deep-reinforcement-learning-approach
#14
Shamim Nemati, Mohammad M Ghassemi, Gari D Clifford, Shamim Nemati, Mohammad M Ghassemi, Gari D Clifford, Gari D Clifford, Mohammad M Ghassemi
Misdosing medications with sensitive therapeutic windows, such as heparin, can place patients at unnecessary risk, increase length of hospital stay, and lead to wasted hospital resources. In this work, we present a clinician-in-the-loop sequential decision making framework, which provides an individualized dosing policy adapted to each patient's evolving clinical phenotype. We employed retrospective data from the publicly available MIMIC II intensive care unit database, and developed a deep reinforcement learning algorithm that learns an optimal heparin dosing policy from sample dosing trails and their associated outcomes in large electronic medical records...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227053/the-effects-of-deep-network-topology-on-mortality-prediction
#15
Hao Du, Mohammad M Ghassemi, Mengling Feng, Hao Du, Mohammad M Ghassemi, Mengling Feng, Mengling Feng, Hao Du, Mohammad M Ghassemi
Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even playing Go. The application of deep-learning to problems in healthcare, however, has gained attention only in recent years, and it's ultimate place at the bedside remains a topic of skeptical discussion. While there is a growing academic interest in the application of Machine Learning (ML) techniques to clinical problems, many in the clinical community see little incentive to upgrade from simpler methods, such as logistic regression, to deep learning...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227051/optimal-decision-support-rules-improve-personalize-warfarin-treatment-outcomes
#16
Chih-Lin Chi, Kourosh Ravvaz, John Weissert, Peter J Tonellato, Chih-Lin Chi, Kourosh Ravvaz, John Weissert, Peter J Tonellato, Chih-Lin Chi, Kourosh Ravvaz, John Weissert, Peter J Tonellato
We tested optimization-based approaches to generate decision support rules used to improve personalized warfarin treatment based on clinical and genetic characteristics. Our approach simulated warfarin treatment outcomes using five existing treatment plans for clinical avatars (virtual patients). We used individual clinical avatar Time-in-Therapeutic-Range to represent the two-sided adverse risk to bleeding (over dosed - above therapeutic range) and thrombosis (under dosed - below therapeutic range) and as the objective function in the optimization to minimize overall risk...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227033/advanced-analytics-for-outcome-prediction-in-intensive-care-units
#17
Ali Jalali, Dieter Bender, Mohamed Rehman, Vinay Nadkanri, C Nataraj, Ali Jalali, Dieter Bender, Mohamed Rehman, Vinay Nadkanri, C Nataraj, Mohamed Rehman, Ali Jalali, Vinay Nadkanri, Dieter Bender, C Nataraj
In this paper we present a new expert knowledge based clinical decision support system for prediction of intensive care units outcome based on the physiological measurements collected during the first 48 hours of the patient's admission to the ICU. The developed CDSS algorithm is composed of several stages. First, we categorize the collected data based on the physiological organ that they represent. We then extract clinically relevant features from each data category and then rank these features based on their mutual information with the outcome...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227019/prediction-using-patient-comparison-vs-modeling-a-case-study-for-mortality-prediction
#18
Mark Hoogendoorn, Ali El Hassouni, Kwongyen Mok, Marzyeh Ghassemi, Peter Szolovits, Mark Hoogendoorn, Ali El Hassouni, Kwongyen Mok, Marzyeh Ghassemi, Peter Szolovits, Kwongyen Mok, Ali El Hassouni, Peter Szolovits, Marzyeh Ghassemi, Mark Hoogendoorn
Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227006/occurrence-of-elevated-shock-index-in-acute-patients-and-development-of-a-proportional-shock-index-metric
#19
Thomas Schmidt, Annmarie Lassen, Uffe Kock Wiil, Thomas Schmidt, Annmarie Lassen, Uffe Kock Wiil, Uffe Kock Wiil, Thomas Schmidt, Annmarie Lassen
Although shock index, as the ratio between heart rate and systolic blood pressure, is a well-recognized predictor for adverse outcomes, it is seldom integrated into clinical evaluation procedures as it requires on-the-fly evaluation of multiple terms. In this paper, we investigate the prevalence of elevated shock index in emergency department patients through an analysis of automatic heart rate and blood pressure readings from 809 admissions to an acute bedside ward at a large Danish hospital. The analysis is conducted by evaluating differences in terms of 30 day mortality...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226899/nanoporous-membrane-robustness-stability-in-small-form-factor-microfluidic-filtration-system
#20
Dean G Johnson, Sabrina Pan, Andrew Hayden, James L McGrath, Dean G Johnson, Sabrina Pan, Andrew Hayden, James L McGrath, Andrew Hayden, Sabrina Pan, Dean G Johnson, James L McGrath
The development of wearable hemodialysis (HD) devices that replace center-based HD holds the promise to improve both outcomes and quality-of-life for patients with end-stage-renal disease (ERD). A prerequisite for these devices is the development of highly efficient membranes that can achieve high toxin clearance in small footprints. The ultrathin nanoporous membrane material developed by our group is orders of magnitude more permeable than conventional HD membranes. We report on our progress making a prototype wearable dialysis unit...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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