Rethink Automatic Treatment of Polyps

Ob Gyn News ◽  
2011 ◽  
Vol 46 (7) ◽  
pp. 10
Author(s):  
ALICE GOODMAN
Keyword(s):  
Automatic Treatment

scholarly journals Automatic treatment planning for VMAT‐based total body irradiation using Eclipse scripting

2021 ◽  
Vol 22 (3) ◽  
pp. 119-130
Author(s):  
Jose R. Teruel ◽  
Sameer Taneja ◽  
Paulina E. Galavis ◽  
K. Sunshine Osterman ◽  
Allison McCarthy ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Total Body Irradiation ◽  
Total Body ◽  
Automatic Treatment

scholarly journals Precision of continuous GPS velocities from statistical analysis of synthetic time series

2018 ◽  
Author(s):  
Christine Masson ◽  
Stephane Mazzotti ◽  
Philippe Vernant
Keyword(s):  
Time Series ◽  
Extreme Values ◽  
Regression Tree ◽  
Simple Method ◽  
Position Time Series ◽  
Gps Velocities ◽  
Synthetic Time Series ◽  
Continuous Gps ◽  
Automatic Treatment ◽  
Gps Noise

Abstract. We use statistical analyses of synthetic position time series to estimate the potential precision of GPS velocities. The synthetic series represent the standard range of noise, seasonal, and position offset characteristics, leaving aside extreme values. This analysis is combined with a new simple method for automatic offset detection that allows an automatic treatment of the massive dataset. Colored noise and the presence of offsets are the primary contributor to velocity variability. However, regression tree analyses show that the main factors controlling the velocity precision are first the duration of the series, followed by the presence of offsets and the noise (dispersion and spectral index). Our analysis allows us to propose guidelines, which can be applied to actual GPS data, that constrain the velocity accuracies (expressed as 95 % confidence limits) based on simple parameters: (1) Series durations over 8.0 years result in high velocity accuracies in the horizontal (0.2 mm yr−1) and vertical (0.5 mm yr−1); (2) Series durations of less than 4.5 years cannot be used for high-precision studies since the horizontal accuracy is insufficient (over 1.0 mm yr−1); (3) Series of intermediate durations (4.5–8.0 years) are associated with an intermediate horizontal accuracy (0.6 mm yr-1) and a poor vertical one (1.3 mm yr−1), unless they comprise no offset. Our results suggest that very long series durations (over 15–20 years) do not ensure a better accuracy compare to series of 8–10 years, due to the noise amplitude following a power-law dependency on the frequency. Thus, better characterizations of long-period GPS noise and pluri-annual environmental loads are critical to further improve GPS velocity precisions.

scholarly journals Sensor‐based wearable system for the detection and automatic treatment of nocturnal hypoglycaemia

2018 ◽  
Vol 5 (6) ◽  
pp. 239-241 ◽  
Author(s):  
Somia Sahraoui ◽  
Sofiane Sahraoui ◽  
Oussama Benbousa ◽  
Ahmed‐Sami Berkani ◽  
Azeddine Bilami
Keyword(s):  
Nocturnal Hypoglycaemia ◽  
Wearable System ◽  
Automatic Treatment

Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique

2018 ◽  
Vol 46 (1) ◽  
pp. 370-381 ◽  
Author(s):  
Jiawei Fan ◽  
Jiazhou Wang ◽  
Zhi Chen ◽  
Chaosu Hu ◽  
Zhen Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Treatment Planning ◽  
Dose Distribution ◽  
Three Dimensional ◽  
Learning Technique ◽  
Automatic Treatment

Tree-based exploration of the optimization objectives for automatic cervical cancer IMRT treatment planning

2021 ◽  
pp. 20210214
Author(s):  
Hanlin Wang ◽  
Ruoxi Wang ◽  
Jiacheng Liu ◽  
Jian Zhang ◽  
Kaining Yao ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Spinal Cord ◽  
Femoral Head ◽  
Treatment Planning ◽  
Planning Process ◽  
Conformity Index ◽  
Plan Quality ◽  
The Mean ◽  
Automatic Treatment ◽  
Better Than

Objectives: To develop and evaluate a practical automatic treatment planning method for Intensity-Modulated Radiation Therapy (IMRT) in cervical cancer cases. Methods: A novel algorithm named as Optimization Objectives Tree Search Algorithm (OOTSA) was proposed to emulate the planning optimization process and achieve a progressively improving IMRT plan, based on the Eclipse Scripting Application Programming Interface (ESAPI). Thirty previously treated cervical cancer cases were selected from the clinical database and comparison was made between the OOTSA-generated plans and clinical treated plans and RapidPlan-based (RP) plans. Results: In clinical evaluation, compared with plan scores of the clinical plans and the RP plans, 22 and 26 of the OOTSA plans were considered as clinically improved in terms of plan quality, respectively. The average conformity index (CI) for the PTV in the OOTSA plans was 0.86 ± 0.01 (mean ± 1 standard deviation), better than those in the RP plans (0.83 ± 0.02) and the clinical plans (0.71 ± 0.11). Compared with the clinical plans, the mean doses of femoral head, rectum, spinal cord and right kidney in the OOTSA plans were reduced by 2.34 ± 2.87 Gy, 1.67 ± 2.10 Gy, 4.12 ± 6.44 Gy and 1.15 ± 2.67 Gy. Compared with the RP plans, the mean doses of femoral head, spinal cord, right kidney and small intestine in the OOTSA plans were reduced by 3.31 ± 1.55 Gy, 4.25 ± 3.69 Gy, 1.54 ± 2.23 Gy and 3.33 ± 1.91 Gy, respectively. In the OOTSA plans, the mean dose of bladder was slightly increased, with 2.33 ± 2.55 Gy (versus clinical plans) and 1.37 ± 1.74 Gy (versus RP plans). The average elapsed time of OOTSA and clinical planning were 59.2 ± 3.47 min and 76.53 ± 5.19 min. Conclusions: The plans created by OOTSA have been shown marginally better than the manual plans, especially in preserving OARs. In addition, the time of automatic treatment planning has shown a reduction compared to a manual planning process, and the variation of plan quality was greatly reduced. Although improvement on the algorithm is warranted, this proof-of-concept study has demonstrated that the proposed approach can be a practical solution for automatic planning. Advances in knowledge: The proposed method is novel in the emulation strategy of the physicists’ iterative operation during the planning process. Based on the existing optimizers, this method can be a simple yet effective solution for automated IMRT treatment planning.

EIS for Consumers Classification and Support Decision Making in a Power Utility Database

2011 ◽  
pp. 103-118
Author(s):  
Juan Ignacio Guerrero Alonso ◽  
Carlos León de Mora ◽  
Félix Biscarri Triviño ◽  
Iñigo Monedero Goicoechea ◽  
Jesús Biscarri Triviño ◽  
...  
Keyword(s):  
New Technologies ◽  
Storage System ◽  
System Capacity ◽  
Access Time ◽  
Enterprise Information System ◽  
Enterprise Information ◽  
Power Utility ◽  
Enterprise Information Systems ◽  
Automatic Treatment

The increasing of the storage system capacity and the reduction of the access time have allowed the development of new technologies which have afforded solutions for the automatic treatment of great databases. In this chapter a methodology to create Enterprise Information Systems which are capable of using all information available about customers is proposed. As example of utilization of this methodology, an Enterprise Information System for classification of customer problems is proposed. This EIS implements several technologies. Data Warehousing and Data Mining are two technologies which can analyze automatically corporative databases. Integration of these two technologies is proposed by the present work together with a rule based expert system to classify the utility consumption through the information stored in corporative databases.

scholarly journals Fully Automatic Treatment Planning for External-Beam Radiation Therapy of Locally Advanced Cervical Cancer: A Tool for Low-Resource Clinics

2019 ◽  
pp. 1-9
Author(s):  
Kelly Kisling ◽  
Lifei Zhang ◽  
Hannah Simonds ◽  
Nazia Fakie ◽  
Jinzhong Yang ◽  
...  
Keyword(s):  
United States ◽  
South Africa ◽  
Cervical Cancer ◽  
Treatment Planning ◽  
South African ◽  
The United States ◽  
Ct Scans ◽  
Low Resource ◽  
Fully Automatic ◽  
Automatic Treatment

Purpose The purpose of this study was to validate a fully automatic treatment planning system for conventional radiotherapy of cervical cancer. This system was developed to mitigate staff shortages in low-resource clinics. Methods In collaboration with hospitals in South Africa and the United States, we have developed the Radiation Planning Assistant (RPA), which includes algorithms for automating every step of planning: delineating the body contour, detecting the marked isocenter, designing the treatment-beam apertures, and optimizing the beam weights to minimize dose heterogeneity. First, we validated the RPA retrospectively on 150 planning computed tomography (CT) scans. We then tested it remotely on 14 planning CT scans at two South African hospitals. Finally, automatically planned treatment beams were clinically deployed at our institution. Results The automatically and manually delineated body contours agreed well (median mean surface distance, 0.6 mm; range, 0.4 to 1.9 mm). The automatically and manually detected marked isocenters agreed well (mean difference, 1.1 mm; range, 0.1 to 2.9 mm). In validating the automatically designed beam apertures, two physicians, one from our institution and one from a South African partner institution, rated 91% and 88% of plans acceptable for treatment, respectively. The use of automatically optimized beam weights reduced the maximum dose significantly (median, −1.9%; P < .001). Of the 14 plans from South Africa, 100% were rated clinically acceptable. Automatically planned treatment beams have been used for 24 patients with cervical cancer by physicians at our institution, with edits as needed, and its use is ongoing. Conclusion We found that fully automatic treatment planning is effective for cervical cancer radiotherapy and may provide a reliable option for low-resource clinics. Prospective studies are ongoing in the United States and are planned with partner clinics.

Hierarchical classification of large-scale patient records for automatic treatment stratification

2015 ◽  
Vol 19 (4) ◽  
pp. 1234-1245 ◽  
Author(s):  
Kuizhi Mei ◽  
Jinye Peng ◽  
Ling Gao ◽  
Naiquan Zheng ◽  
Jianping Fan
Keyword(s):  
Large Scale ◽  
Hierarchical Classification ◽  
Patient Records ◽  
Automatic Treatment

TH-E-BRCD-01: Automatic Treatment Planning - an MCO Perspective

2012 ◽  
Vol 39 (6Part30) ◽  
pp. 4007-4007
Author(s):  
D Craft
Keyword(s):  
Treatment Planning ◽  
Automatic Treatment
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