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About 6,993 papers for “treatment decision algorithm”
Peter J. Kitonsa (7037504), Bernard Kikaire (16913730), Peter Wambi (17451594) et al. · Figshare · 2025
Treatment decision algorithms (TDAs) revised in 2022 by the World Health Organisation to improve TB diagnosis in children in settings without chest x-ray. (TIF)
Cited by 0Open access
Peter J. Kitonsa (7037504), Bernard Kikaire (16913730), Peter Wambi (17451594) et al. · Figshare · 2025
Treatment decision algorithms (TDAs) revised in 2022 by the World Health Organisation to improve TB diagnosis in children in settings with chest x-ray. (TIF)
Cited by 0Open access
Nick Panay · Menopause international · 2012
The aim of this short paper will be to guide the clinician through the plethora of possible interventions to help them to individualize treatment for their patients with PMS. The discussion will highlight management principles rather than evidence per se. It uses as its basis an updated version of the treatment algorithm published by the RCOG in its Green Top Guideline no. 48 on the management of PMS.
Cited by 17
Nusrat Jahan, Rezvi Shahariar · Indonesian Journal of Electrical Engineering and Computer Science · 2020
<span>Machine learning approaches are progressively successful in image based analysis such as different diseases prediction as well as level of risk assessment etc. In this paper, image based data analysis with machine learning technique were used for fertilizer treatment of maize. We address this issue as our country depend on agricultural field rather than others. Maize has a bright future. To predict fertilizer treatment of maize dataset were comprised of ground coverage region which highlights the green pixels of a maize image. For calculating green pixels from an image we used “Can Eye” tool. The achievement of machine learning approaches is highly dependent on quality and quantity of the dataset which is used for training the machine for better classification result. For this perseverance, we collected images from the maize field directly. Then processed those images and classified the data into four classes (Less Nitrogen=-N, Less Phosphorus=-P, Less Potassium=-K and NPK) to train our machine using decision tree algorithm to predict fertilizer treatment. We got 93% classification accuracy for decision tree. Finally, the outcome of this paper is the fertilizer treatment of a maize field based on the ground cover percentage, and we implemented this whole work using an android platform because of the availability of android mobile phone throughout the world.</span>
Cited by 11Open access
Rina Triasih, Finny Fitry Yani, Dewi Wulandari et al. · Preprints.org · 2025
Clinical algorithms for child tuberculosis (TB) are a valuable guide for healthcare-workers to initiate treatment. We evaluated the 2022 WHO treatment decision algorithm and developed a new Indonesia algorithm for child TB. We conducted a retrospective study at 10 hospitals in Indonesia, involving children (0-10 years), who were evaluated for TB diagnosis in 2022. A panel of child TB experts used participant’s records to make a diagnosis using the 2022 WHO algorithm and the 2016 Indonesian algorithm. We assessed agreement between the diagnosis made by the attending doctor and those determined by the expert panel. A new Indonesia guideline was developed based on the findings and consensus of various stakeholders. Of 523 eligible children, 371 (70.9%) were diagnosed with TB by the attending doctors, 295 (56.4%) by WHO algorithm, and 246 (47%) by Indonesia algorithm. The Cohen’s Kappa of TB diagnosis was: attending doctor vs WHO algorithm (0.27), attending doctor vs Indonesia algorithm (0.45), and WHO algorithm vs Indonesia algorithm (0.42). A detailed review of both algorithms revealed limitations for implementation. An algorithmic approach for child TB diagnosis may not be universally applicable or implementable due to variable access to diagnostic tests and wide variety of clinical presentations.
Cited by 1Open access
Lorena Sabonet Morente, Ana I. Guzmán León, P. Reina et al. · Preprints.org · 2021
Background Cesarean scar ectopic pregnancies are a rare form of extrauterine pregnancies, yet their incidence has increased along with the rise in the number of cesarean deliveries. As with other ectopic pregnancies, cesarean scar ectopic pregnancies pose a greater risk for maternal hemorrhage and ultimately maternal mortality. Case presentation We present a series of clinical cases of cesarean scar ectopic pregnancy diagnosed by transvaginal ultrasonography. Each patient received an individualized treatment: the rate of success depended on the particular maternal condition in each case. Due to the low frequency of this entity, there are no clear protocols for its treatment and thus there are numerous options for treatment and follow up: expectant management, medical therapy, surgical intervention, uterine artery embolization or a combined approach. Each method has different levels of success and is dependent on the surgeon&rsquo;s skill and patient presentation. The transvaginal ultrasound is necessary to obtain the fine details of the gestation sac and its relation to the scar and must be followed by a meticulous abdominal scan with a full bladder. Conclusion Herein, we present a rare pathological phenomenon whose frequency is on the rise, and for which transvaginal ultrasound and flow doppler provide high diagnostic accuracy. Early diagnosis of cesarean scar ectopic pregnancies offers treatment options to that may help avoid uterine rupture and bleeding, thus preserving the uterus and future fertility.
Cited by 1Open access
Case Medical Research · Case Medical Research · 2020
Cited by 0
Weijie Xu, Jincheng Ge · Mathematical Modeling and Algorithm Application · 2024
Drug testing has always been an effective way to test drug effects and reduce drug costs. It is also a necessary measure for testing in the clinical stage. The results of drug testing will provide an important basis for the listing of new drugs, which is of great significance for promoting the development of medical science and improving the quality of life of patients. This article uses the decision tree algorithm to achieve effective allocation of drugs, improve the accuracy of treatment, determine and quantify the patient's key parameter information, including gender, blood pressure, and cholesterol. The model introduces two kinds of algorithm forms of decision tree through information entropy and Gini coefficient, and divides the data set into five kinds of decision trees through the algorithm, and the accuracy values all reach above 85%, and wait until the approximate accuracy effect under the condition of specifying random numbers, which provides scientific analysis for analyzing patients' choice of drugs.
Cited by 0Open access
Antonov Av, Ishutin EIu, Guliev Rn · PubMed · 2012
The article presents an algorithm of diagnostics and treatment of renal cysts and other liquid neoplasms of the retroperitoneal space on an analysis of 270 case histories. The algorithm takes into account the achievements of modern medical technologies developed in the recent years. The application of the proposed algorithm must elevate efficiency of the diagnosis and quality of treatment of patients with renal cysts.
Cited by 0
A. V. Antonov, Ye. Yu. Ishutin, Rasid Guliev · SHILAP Revista de lepidopterología · 2018
The article presents an algorithm of diagnostics and treatment of renal cysts and other liquid neoplasms of the retroperitoneal space on an analysis of 270 case histories. The algorithm takes into account the achievements of modern medical technologies developed in the recent years. The application of the proposed algorithm must elevate efficiency of the diagnosis and quality of treatment of patients with renal cysts.
Cited by 0Open access
Peter Brønnum Nielsen, Søren Lundbye‐Christensen, Lars Hvilsted Rasmussen et al. · Thrombosis Research · 2014
Cited by 10
Xuequan Zhu, Rou Zhong, Xu Chen et al. · Journal of Psychiatric Research · 2026
Week 4 emerges as a key decision point for escitalopram-treated MDD patients, where integration of baseline profiles, early response patterns, and dose parameters allows timely intervention. Our decision tree framework offers a methodological approach for dynamic decision points that warrant prospective validation and extension to other antidepressants.
Cited by 0Open access
Lorena Sabonet Morente, Ana I. Guzmán León, María Pilar Espejo-Reina et al. · Medicina · 2021
<i>Background</i>: Cesarean scar ectopic pregnancies are a rare form of extrauterine pregnancies, yet their incidence has increased along with the rise in the number of cesarean deliveries. As with other ectopic pregnancies, cesarean scar ectopic pregnancies pose a greater risk for maternal hemorrhage and ultimately maternal mortality. <i>Case presentation</i>: We present a series of clinical cases of cesarean scar ectopic pregnancy diagnosed by transvaginal ultrasonography. Each patient received an individualized treatment: the rate of success depended on the particular maternal condition in each case. Due to the low frequency of this entity, there are no clear protocols for its treatment and thus there are numerous options for treatment and follow-up: expectant management, medical therapy, surgical intervention, uterine artery embolization or a combined approach. Each method has different levels of success and is dependent on the surgeon's skill and patient presentation. A transvaginal ultrasound is necessary to obtain the fine details of the gestation sac and its relation to the scar and must be followed by a meticulous abdominal scan with a full bladder. <i>Conclusion</i>: Herein, we present a rare pathological phenomenon whose frequency is on the rise, and for which transvaginal ultrasound and flow Doppler provide high diagnostic accuracy. Early diagnosis of cesarean scar ectopic pregnancies offers treatment options that may help avoid uterine rupture and bleeding, thus preserving the uterus and future fertility.
Cited by 26Open access
Doubleday, Kevin, Zhou, Hua, Fu, Haoda et al. · Figshare · 2018
With new treatments and novel technology available, precision medicine has become a key topic in the new era of healthcare. Traditional statistical methods for precision medicine focus on subgroup discovery through identifying interactions between a few markers and treatment regimes. However, given the large scale and high dimensionality of modern datasets, it is difficult to detect the interactions between treatment and high-dimensional covariates. Recently, novel approaches have emerged that seek to directly estimate individualized treatment rules (ITR) via maximizing the expected clinical reward by using, for example, support vector machines (SVM) or decision trees. The latter enjoys great popularity in clinical practice due to its interpretability. In this article, we propose a new reward function and a novel decision tree algorithm to directly maximize rewards. We further improve a single tree decision rule by an ensemble decision tree algorithm, ITR random forests. Our final decision rule is an average over single decision trees and it is a soft probability rather than a hard choice. Depending on how strong the treatment recommendation is, physicians can make decisions based on our model along with their own judgment and experience. Performance of ITR forest and tree methods is assessed through simulations along with applications to a randomized controlled trial (RCT) of 1385 patients with diabetes and an EMR cohort of 5177 patients with diabetes. ITR forest and tree methods are implemented using statistical software R (<i>https://github.com/kdoub5ha/ITR.Forest</i>). Supplementary materials for this article are available online.
Cited by 0Open access
Amanda C. Filiberto, Salvatore T. Scali, Suzannah Patterson et al. · Annals of Vascular Surgery · 2021
Cited by 20
Kernel Networks Inc. · Case Medical Research · 2019
Cited by 0
Moalla, Salma · European Society of Radiology · 2016
Cited by 0Open access
Voltan Garofo, Karen, 1977- · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2021
Orientador: Mauricio Etchebehere
Cited by 0Open access
S. Sibai, F. Bellarbre, M. Priner et al. · European Geriatric Medicine · 2013
Cited by 0
Zdzisław Pawlak, Roman Słowiński, Roman Słowiński et al. · Our Digital Library (Warsaw University of Technology) · 1987
W: Bulletin of the Polish Academy of Sciences, Biological Sciences, 34(9-10):227-246, 1987.
Cited by 39