scholarly journals Discovery of Genes Positively Modulating Treatment Effect Using Potential Outcome Framework and Bayesian Update

2021 ◽  
Author(s):  
Young Keun Lee ◽  
Jisoo Kim ◽  
Sung Wook Seo
Keyword(s):  
Cancer Genomics ◽  
Search Algorithm ◽  
Medical Center ◽  
External Validation ◽  
Gene Mutations ◽  
Rank Test ◽  
Test Analysis ◽  
Potential Outcome ◽  
Outcome Framework ◽  
Causal Genes

Abstract BackgroundThe recent explosion of cancer genomics provides extensive information about mutations and gene expression changes in cancer. However, most of the identified gene mutations are not clinically utilized. It remains uncertain whether the presence of a certain genetic alteration will affect treatment response. Conventional statistics have limitations for causal inferences and are hard to gain sufficient power in genomic datasets. Here, we developed and evaluated an algorithm for searching the causal genes that maximize the effect of the treatment.MethodsThe algorithm was developed based on the potential outcome framework and Bayesian posterior update. The precision of the algorithm was validated using a simulation dataset. The algorithm was implemented to a cBioPortal dataset. The genes discovered by the algorithm were externally validated within CancerSCAN screening data from Samsung Medical Center.ResultsSimulation data analysis showed that the C-search algorithm was able to identify nine causal genes out of ten. The C-search algorithm shows the discovery rate rapidly increasing until the 1500 number of data. Meanwhile, the log-rank test shows a slower increase in performance. The C-search algorithm was able to suggest nine causal genes from the cBioPortal Metabric dataset. Treating the patients with the causal genes are associated with better survival outcome in both the cBioPortal dataset and the CancerSCAN dataset which is used for external validation.ConclusionsOur C-search algorithm demonstrated better performance to identify causal effects of the genes than multiple rog-rank test analysis especially within a limited number of data. The result suggests that the C-search can discover the causal genes from various genetic datasets, where the number of samples is limited compared to the number of variables.

scholarly journals Effectiveness of transfer learning for enhancing tumor classification with a convolutional neural network on frozen sections

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Young-Gon Kim ◽  
Sungchul Kim ◽  
Cristina Eunbee Cho ◽  
In Hye Song ◽  
Hee Jin Lee ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Transfer Learning ◽  
Frozen Section ◽  
Medical Center ◽  
External Validation ◽  
Model Performance ◽  
Classification Model ◽  
Training Dataset

AbstractFast and accurate confirmation of metastasis on the frozen tissue section of intraoperative sentinel lymph node biopsy is an essential tool for critical surgical decisions. However, accurate diagnosis by pathologists is difficult within the time limitations. Training a robust and accurate deep learning model is also difficult owing to the limited number of frozen datasets with high quality labels. To overcome these issues, we validated the effectiveness of transfer learning from CAMELYON16 to improve performance of the convolutional neural network (CNN)-based classification model on our frozen dataset (N = 297) from Asan Medical Center (AMC). Among the 297 whole slide images (WSIs), 157 and 40 WSIs were used to train deep learning models with different dataset ratios at 2, 4, 8, 20, 40, and 100%. The remaining, i.e., 100 WSIs, were used to validate model performance in terms of patch- and slide-level classification. An additional 228 WSIs from Seoul National University Bundang Hospital (SNUBH) were used as an external validation. Three initial weights, i.e., scratch-based (random initialization), ImageNet-based, and CAMELYON16-based models were used to validate their effectiveness in external validation. In the patch-level classification results on the AMC dataset, CAMELYON16-based models trained with a small dataset (up to 40%, i.e., 62 WSIs) showed a significantly higher area under the curve (AUC) of 0.929 than those of the scratch- and ImageNet-based models at 0.897 and 0.919, respectively, while CAMELYON16-based and ImageNet-based models trained with 100% of the training dataset showed comparable AUCs at 0.944 and 0.943, respectively. For the external validation, CAMELYON16-based models showed higher AUCs than those of the scratch- and ImageNet-based models. Model performance for slide feasibility of the transfer learning to enhance model performance was validated in the case of frozen section datasets with limited numbers.

A Survey on Causal Inference

2021 ◽  
Vol 15 (5) ◽  
pp. 1-46
Author(s):  
Liuyi Yao ◽  
Zhixuan Chu ◽  
Sheng Li ◽  
Yaliang Li ◽  
Jing Gao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Causal Inference ◽  
Observational Data ◽  
Causal Effect ◽  
Research Direction ◽  
Estimation Methods ◽  
Potential Outcome ◽  
Outcome Framework ◽  
Benchmark Datasets ◽  
Inference Methods

Causal inference is a critical research topic across many domains, such as statistics, computer science, education, public policy, and economics, for decades. Nowadays, estimating causal effect from observational data has become an appealing research direction owing to the large amount of available data and low budget requirement, compared with randomized controlled trials. Embraced with the rapidly developed machine learning area, various causal effect estimation methods for observational data have sprung up. In this survey, we provide a comprehensive review of causal inference methods under the potential outcome framework, one of the well-known causal inference frameworks. The methods are divided into two categories depending on whether they require all three assumptions of the potential outcome framework or not. For each category, both the traditional statistical methods and the recent machine learning enhanced methods are discussed and compared. The plausible applications of these methods are also presented, including the applications in advertising, recommendation, medicine, and so on. Moreover, the commonly used benchmark datasets as well as the open-source codes are also summarized, which facilitate researchers and practitioners to explore, evaluate and apply the causal inference methods.

scholarly journals External validation of the R.I.R.S. scoring system to predict stone-free rate after retrograde intrarenal surgery

BMC Urology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Cong Wang ◽  
ShouTong Wang ◽  
Xuemei Wang ◽  
Jun Lu
Keyword(s):  
Scoring System ◽  
Kidney Stone ◽  
Medical Center ◽  
External Validation ◽  
Retrograde Intrarenal Surgery ◽  
Stone Burden ◽  
Stone Free Rate ◽  
Stone Density ◽  
Free Rate ◽  
Free Status

Abstract Background The R.I.R.S. scoring system is defined as a novel and straightforward scoring system that uses the main parameters (kidney stone density, inferior pole stones, stone burden, and renal infundibular length) to identify most appropriate patients for retrograde intrarenal surgery (RIRS). We strived to evaluate the accuracy of the R.I.R.S. scoring system in predicting the stone-free rate (SFR) after RIRS. Methods In our medical center, we retrospectively analyzed charts of patients who had, between September 2018 and December 2019, been treated by RIRS for kidney stones. A total of 147 patients were enrolled in the study. Parameters were measured for each of the four specified variables. Results Stone-free status was achieved in 105 patients (71.43%), and 42 patients had one or more residual fragments (28.57%). Differences in stone characteristics, including renal infundibulopelvic angle, renal infundibular length, lower pole stone, kidney stone density, and stone burden were statistically significant in patients whether RIRS achieved stone-free status or not (P < 0.001, P: 0.005, P < 0.001, P < 0.001, P: 0.003, respectively). R.I.R.S. scores were significantly lower in patients treated successfully with RIRS than patients in which RIRS failed (P < 0.001). Binary logistic regression analyses revealed that R.I.R.S. scores were independent factors affecting RIRS success (P = 0.033). The area under the curve of the R.I.R.S. scoring system was 0.737. Conclusions Our study retrospectively validates that the R.I.R.S. scoring system is associated with SFR after RIRS in the treatment of renal stones, and can predict accurately.

Update and external validation of a multivariable prediction model for tube feeding dependency for at least four weeks during chemoradiotherapy for head and neck cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 6040-6040
Author(s):  
Anna C. H. Willemsen ◽  
Annemieke Kok ◽  
Laura W.J. Baijens ◽  
J. P. De Boer ◽  
Remco de Bree ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Radiation Dose ◽  
The Netherlands ◽  
Prediction Model ◽  
Head And Neck ◽  
Neck Cancer ◽  
Predictive Value ◽  
Medical Center ◽  
External Validation ◽  
Tube Feeding

6040 Background: Patients who receive chemoradiation or bioradiation (CRT/BRT) for locally advanced head and neck squamous cell carcinoma (LAHNSCC) often experience high toxicity rates, which may interfere with oral intake, leading to (temporary) tube feeding (TF) dependency. International guidelines recommend gastrostomy insertion when the expected use of TF exceeds four weeks. In this study we aimed to update and externally validate a prediction model to identify patients in need for TF for at least four weeks, meeting the international criteria for prophylactic gastrostomy insertion. Methods: This retrospective multicenter cohort study was performed in four tertiary referral head and neck cancer centers in the Netherlands. The prediction model was developed using data from the University Medical Center Utrecht and the Netherlands Cancer Institute. The model was externally validated in patients from the Maastricht University Medical Center and Radboud University Medical Center. The primary endpoint was TF, initiated during or within 30 days after completion of CRT/BRT, and administered for at least four weeks. Potential predictors were retrieved from patient medical records and radiotherapy dose-volume parameters were calculated. Results: The developmental and validation cohort included 409 and 334 patients respectively. Multivariable analysis showed significant predictive value (p < 0.05) for adjusted diet at start of CRT/BRT, percentage weight change prior to treatment initiation, WHO performance status, tumor-site, nodal stage, mean radiation dose to the contralateral parotid gland, and mean radiation dose to the oral cavity. The area under the receiver operating characteristics curve for the updated model was 0.73 and after external validation 0.64. Positive and negative predictive value at 90% cut off were 80.0% and 48.2% respectively. Conclusions: This externally validated prediction model to estimate TF-dependency for at least four weeks in LAHNSCC patients performs well. This model, which will be presented, can be used in clinical practice to guide personalized decision making on prophylactic gastrostomy insertion.

A group sequential design and sample size estimation for an immunotherapy trial with a delayed treatment effect

2020 ◽  
pp. 096228022098078
Author(s):  
Bosheng Li ◽  
Liwen Su ◽  
Jun Gao ◽  
Liyun Jiang ◽  
Fangrong Yan
Keyword(s):  
Sample Size ◽  
Treatment Effect ◽  
Search Algorithm ◽  
Rank Test ◽  
Group Sequential Design ◽  
Group Sequential ◽  
Delayed Treatment ◽  
Maximum Sample Size ◽  
Analytical Estimation ◽  
Immunotherapy Trial

A delayed treatment effect is often observed in the confirmatory trials for immunotherapies and is reflected by a delayed separation of the survival curves of the immunotherapy groups versus the control groups. This phenomenon makes the design based on the log-rank test not applicable because this design would violate the proportional hazard assumption and cause loss of power. Thus, we propose a group sequential design allowing early termination on the basis of efficacy based on a more powerful piecewise weighted log-rank test for an immunotherapy trial with a delayed treatment effect. We present an approach on the group sequential monitoring, in which the information time is defined based on the number of events occurring after the delay time. Furthermore, we developed a one-dimensional search algorithm to determine the required maximum sample size for the proposed design, which uses an analytical estimation obtained by the inflation factor as an initial value and an empirical power function calculated by a simulation-based procedure as an objective function. In the simulation, we tested the unstable accuracy of the analytical estimation, the consistent accuracy of the maximum sample size determined by the search algorithm and the advantages of the proposed design on saving sample size.

scholarly journals PERBANDINGAN EFEKTIVITAS CIRCULO MASSAGE DANSPORT MASSAGE DALAM MENGATASI KELELAHAN KERJAKARYAWAN LAKI - LAKI GADJAH MADA MEDICAL CENTER

MEDIKORA ◽  
2015 ◽  
Author(s):  
Kunto Prastowo dan Novita Intan Arovah
Keyword(s):  
Medical Center ◽  
Rank Test ◽  
P Value ◽  
Purposive Sampling ◽  
Signed Rank ◽  
Signed Rank Test

Penelitian ini bertujuan mengetahui perbandingan efektivitas circulo massage dansport massage dalam mengatasi kelelahan kerja karyawan Gadjah Mada Medical Center.Penelitian ini merupakan penelitian pra eksperimen dengan desain treatment bysubjects. Subjek penelitian ini adalah 15 karyawan laki-laki GMC yang direkrut denganteknik purposive sampling. Subjek diberi dua perlakuan yakni circulo massage dan sportmassage dengan selang waktu + 1 minggu. Sebelum dan sesudah perlakuan massagedilakukan pengukuran tingkat kelelahan kerja dengan menggunakan kuisioner kelelahankerja yang telah diujicoba dan dinyatakan valid dan koefisien reliabilitas sebesar 0,779.Teknik analisis data yang digunakan dalam penelitian ini adalah analisis deskriptif,analisis efektivitas (nilai posttest-pretest)/ pretest) dan uji beda dengan menggunakan ujiwilcoxon signed rank test dengan taraf signifikansi 5 %.Hasil penelitian menunjukkan bahwa nilai rata-rata pretest dan posttest kelelahankerja pada perlakuan circulo massage adalah 29 dan 20,53, uji efektivitas menunjukkanpenurunan 29,20 % (p value: 0,0012). Pada penelitian dengan perlakuan sport massagemenunjukkan bahwa nilai rata-rata pretest dan posttest kelelahan kerja adalah 29,9 dan17,5, uji efektivitas menunjukkan penurunan 41,47 % (p value : 0.0006). Perbandinganantara kelelahan kerja pada perlakuan efektivitas circulo massage dan sport massagemenghasilkan p value: 0,0287. Dapat disimpulkan sport massage lebih efektifdibandingkan circulo massage dalam mengatasi kelelahan kerja pada karyawan laki-lakiGadjah Mada Medical Center.Kata kunci : Circulo massage, sport massage, kelelahan kerja

scholarly journals Hubungan Beban Kerja Perawat Dengan Peran Perawat Anak Dalam Pendampingan Terapi Bermain

JKEP ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 104-113
Author(s):  
Ririn Nur Indah sari ◽  
Sari Windyastuti ◽  
Tri Sakti Widyaningsih
Keyword(s):  
Play Therapy ◽  
Sampling Technique ◽  
Rank Test ◽  
P Value ◽  
Test Statistic ◽  
Cross Sectional ◽  
Test Analysis ◽  
Spearman Rank ◽  
Nurse Workload

Nurse workload is very influential on child play therapy assistance caused by workload excessive workload, lack of facilities and infrastructure, nothing schedule for play therapy and the number of nurses  only 18 nurses, According to theory Gilles with the number of beds 34 needed 29 nurses. The purpose of this research is to know the Relationship of Nurse Workload with The Role of Child’s Nurse in Mentoring Play Therapy in Room Dahlia RSUD Dr. H Sewondo Kendal. This type of research is descriptive correlation with cross sectional. The sampling technique with total sampling, a sample is 18 respondents. Retrieval data using questionnaires and then tested into Spearman Rank test statistic. Based on research found 10 respondents (55,6%) have hard workload and 8 respondents (44,4%) have a light workload. The role of nurses in good categories 5 respondents (27,8%) and categories less is 13 respondents (72,2%). From result of Spearman Rank test analysis, get result of coefficient correlation value -868 in category very strong and obtained p value = 0,000 < 0,05 it’s mean Ha accepted and H0 rejected. There is a relantionship between the nurses workload with the role of child nurses in mentoring play therapy.

scholarly journals The Related Factors To Decreased The New Graduate Nurses Work Stress Level Of In Semarang

2017 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
ARIEF YANTO ◽  
SRI REJEKI
Keyword(s):  
Work Stress ◽  
Stress Measurement ◽  
Medical Center ◽  
Mentoring Programs ◽  
Rank Test ◽  
P Value ◽  
Stressful Situation ◽  
Graduate Nurses ◽  
New Graduate Nurses ◽  
New Graduate

Background: The new graduate nurses have been in a stressful situation about their workplace. The High level of work stress has been decreased the nurse�s motivation in the work, so it will have an impact on the decline the nursing services quality. The new graduate nurses with the work stress will be motivated to quit their jobs. Objective: This study aims to determine the factors associated with decreased job stress of new graduate nurses. Method: This study was a quantitative research. The data was analized with the associative analytic method and cross sectional approach. The population of this study was all new graduate nurses who have had experience for 1-6 months. The sample size is determined by total sampling technique of 30 nurses. The study was conducted at Semarang Medical Center. Work stress measurement using DASS 42 instrument. The analysis process of the data performed using Spearman rank test and multiple linear regression to measure the relation of factors related to work stress. Result: The new graduate nurses work stress has a normal until light category. The average value of new graduate nurses work stress was 27, with the minimum and maximum score 8-40. The factors that have been eligible for the multivariate analysis of new graduate nurses work stress reduction were age and the mentoring programs. The result of the multivariate test showed that nurse ages together with the mentoring program had significant effect to the decreased of new graduate nurses work stress (p-value = 0,007). Discussion: Has increased of ages have been improved adaptability and positive response to stressors. The mentoring was the process of coaching for the new graduate nurses. Mentoring can be used as a support system for new graduate nurses in facing the transition from student to being nurses. The combination of increased the ages and the mentoring programs have been reduced the new graduate nurses work stress.

scholarly journals Estimating the effect of plate discipline using a causal inference framework: an application of the G-computation algorithm

2018 ◽  
Vol 14 (2) ◽  
pp. 37-56
Author(s):  
David Michael Vock ◽  
Laura Frances Boehm Vock
Keyword(s):  
Causal Inference ◽  
Potential Outcome ◽  
Batting Average ◽  
Outcome Framework ◽  
Computation Algorithm ◽  
Using Data ◽  
Correlated Factors

AbstractOffensive performance in baseball depends on a number of correlated factors: the pitches the batter faces, the batter’s choice to swing, and the batter’s hitting ability. Recently a renewed focus on the effect of plate discipline on batter performance has emerged. Plate discipline has traditionally been summarized as the proportion of pitches inside and outside of the strike zone a player swings at; however, there have been few metrics proposed to assess the effect of plate discipline directly on batters’ outcomes. In this paper, we focus on estimating a batter’s performance if he were able to adopt a different plate discipline. Because we wish to assess the effect of a counterfactual plate discipline, we use a potential outcome framework and show how the G-computation algorithm can be used to isolate the effect of plate discipline separately from a batter’s hitting ability or the types of pitches the batter faces. As an example, we implement our approach using data collected with the PITCHf/x system over the 2012–2014 seasons to identify the improvement Starlin Castro would expect to see in offensive performance were he able to adopt Andrew McCutchen’s plate discipline. We estimate that had Castro adopted McCutchen’s discipline his batting average, on-base percentage, and slugging percentage would have increased 0.017 (se = 0.004), 0.040 (se = 0.006), and 0.028 (se = 0.008), respectively.

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