8,477 research outputs found

    Data Mining Approach for Breast Cancer Patient Recovery

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    Breast cancer is the second highest cancer type which attacked Indonesian women. There are several factors known related to encourage an increased risk of breast cancer, but especially in Indonesia that factors often depends on the treatment routinely. This research examines the determinant factors of breast cancer and measures the breast cancer patient data to build the useful classification model using data mining approach.The dataset was originally taken from one of Oncology Hospital in East Java, Indonesia, which consists of 1097 samples, 21 attributes and 2 classes. We used three different feature selection algorithms which are Information Gain, Fisher’s Discriminant Ratio and Chi-square to select the best attributes that have great contribution to the data. We applied Hierarchical K-means Clustering to remove attributes which have lowest contribution. Our experiment showed that only 14 of 21 original attributes have the highest contribution factor of the breast cancer data. The clustering algorithmdecreased the error ratio from 44.48% (using 21 original attributes) to 18.32% (using 14 most important attributes).We also applied the classification algorithm to build the classification model and measure the precision of breast cancer patient data. The comparison of classification algorithms between Naïve Bayes and Decision Tree were both given precision reach 92.76% and 92.99% respectively by leave-one-out cross validation. The information based on our data research, the breast cancer patient in Indonesia especially in East Java must be improved by the treatment routinely in the hospital to get early recover of breast cancer which it is related with adherence of patient

    Effect of Designed Ureteral Stent Instructions on Patient Recovery

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    Context: Ureteral stent placement is performed in up to eighty percent of patients following ureteroscopy. It is associated with significant morbidity, resulting in a reduction in general health function in another eighty percent of patients.Aim: This study aimed to evaluate the effect of designed ureteral stent instructions on patient recovery.Methods: Quasi-experimental (pre/post-test) design was utilized in this study. The study was carried out at the urology department to be followed up through the urology outpatient clinic at Benha University Hospital from the beginning of February 2019 to February 2020 on a purposive sample of 134 patients. Four tools were used to collect the study data. These tools included a structured interview questionnaire to assess patients' knowledge regarding ureteral stents, a ureteral stent symptoms questionnaire, a ureteral stent discomfort test, and a patient's satisfaction assessment form. Results: Showed a mean study sample age of 43.42±6.47, 83.6% were males. The study also showed a statistically significant improvement of the study group’s knowledge in the post-operative and follow-up phases (p<0.017, <0.003), as well as a decrease in total mean score in ureteral stent symptoms and ureteral stent discomfort test (p<0.001), immediately and after designed instructions.Conclusion: Implementing designed instructions for patients with ureteral stents was effective in improving knowledge, a decrease of ureteral stent symptoms, and a decrease in patient discomfort. The study recommended manuals, information booklets, and self-instruction modules developed in areas of ureteral stent management

    Smart and secure medical device gateway for managing patient recovery

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    Patients recuperating from orthopedic surgery require frequent monitoring and hospital visits with a wealth of personal medical data generated both on and off-site, making it challenging to maintain records. This paper discusses a secure blockchain-based data management software to enable safe remote access without compromising patient information. The BlockTrack software developed at our group will be customized to interface with modules for orthopedic recuperation monitoring. Modules can consist of ultrasonic bone health monitoring sensors, connected to relay nodes that can transmit patient data to the BlockTrack mobile app, which then intercepts the information to be stored securely on a cloud-based Blockchain network. Each record will have a unique ID enabled by Blockchain, for secure access and review of patient information by other parties, including doctors and pharmacists. Key findings are discussed with a goal to further develop this solution

    Neural network based patient recovery estimation of a PAM-based rehabilitation robot

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    Rehabilitation robots have shown a promise in aiding patient recovery by supporting them in repetitive, systematic training sessions. A critical factor in the success of such training is the patient’s recovery progress, which can guide suitable treatment plans and reduce recovery time. In this study, a neural network-based approach is proposed to estimate the patient’s recovery, which can aid in the development of an assist-as-needed training strategy for the gait training system. Experimental results show that the proposed method can accurately estimate the external torques generated by the patient to determine their recovery. The estimated patient recovery is used for an impedance control of a 2-DOF robotic orthosis powered by pneumatic artificial muscles, which improves the robot joint compliance coefficients and makes the patient more comfortable and confident during rehabilitation exercises

    Micro-doppler-based in-home aided and unaided walking recognition with multiple radar and sonar systems

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    Published in IET Radar, Sonar and Navigation. Online first 21/06/2016.The potential for using micro-Doppler signatures as a basis for distinguishing between aided and unaided gaits is considered in this study for the purpose of characterising normal elderly gait and assessment of patient recovery. In particular, five different classes of mobility are considered: normal unaided walking, walking with a limp, walking using a cane or tripod, walking with a walker, and using a wheelchair. This presents a challenging classification problem as the differences in micro-Doppler for these activities can be quite slight. Within this context, the performance of four different radar and sonar systems – a 40 kHz sonar, a 5.8 GHz wireless pulsed Doppler radar mote, a 10 GHz X-band continuous wave (CW) radar, and a 24 GHz CW radar – is evaluated using a broad range of features. Performance improvements using feature selection is addressed as well as the impact on performance of sensor placement and potential occlusion due to household objects. Results show that nearly 80% correct classification can be achieved with 10 s observations from the 24 GHz CW radar, whereas 86% performance can be achieved with 5 s observations of sonar

    Genome sequence of Staphylococcus epidermidis strain AU12-03, isolated from an intravascular catheter

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    In recent years, Staphylococcus epidermidis has become a major nosocomial pathogen and the most common cause of intravascular catheter-related bacteremia, which can increase morbidity and mortality and significantly affect patient recovery. We report a draft genome sequence of Staphylococcus epidermidis AU12-03, isolated from an intravascular catheter tip

    A Multicenter, Prospective, Randomized, Contralateral Study of Tissue Liquefaction Liposuction vs Suction-Assisted Liposuction

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    Tissue liquefaction liposuction (TLL) deploys a novel energy source utilizing a stream of warmed, low-pressurized, and pulsed saline to extract fat tissue. Objectives: Compare TLL to suction-assisted liposuction (SAL) to determine which device is more efficient for surgeons and provides better recovery for patients. Methods: Thirty-one adult female patients were followed prospectively in a contralateral study design comparing differences in bruising, swelling, tenderness, and incision appearance ratings between TLL and SAL procedures. Surgical efficiency and appearance of the lipoaspirate were also compared. Results: All 31 patients successfully completed the study. For TLL and SAL procedures, the average volumes of infusion (1.242 vs 1.276 L) and aspirated supernatant fat (704 vs 649 mL) were statistically similar. TLL median fat extraction rate was faster than SAL (35.6 vs 25 mL/min; P < 0.0001), and stroke rate was reduced in TLL vs SAL procedures (48 vs 120 strokes/min; P < 0.0001), and both were statistically significant. The mean total scores for bruising, swelling, treatment site tenderness, and incision appearance were lower, indicating improved patient recovery on the TLL side. Conclusions: TLL and SAL techniques produced comparable volume of fat aspirate. TLL demonstrated a 42% faster fat extraction rate and a 68% reduction in arm movements needed to complete the procedure compared to SAL, both of these differences are statistically significant. The TLL side was noted to have reduced bruising and swelling and improved incision site appearance with less tenderness compared to the SAL side
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