scholarly journals Predicting the Side Effects of Drugs using Matrix Factorization on Spontaneous Reports Database

2021 ◽  
Author(s):  
Kohei Fukuto ◽  
Tatsuya Takagi ◽  
Yu-Shi Tian
Keyword(s):  
Side Effects ◽  
Matrix Factorization ◽  
Side Effect ◽  
Cold Start ◽  
Computational Techniques ◽  
Spontaneous Reports ◽  
Proposed Model ◽  
Feedback Data ◽  
The Impact ◽  
Cold Start Problem

Abstract Background Drugs with severe side effects can be threatening to patients and compromise pharmaceutical companies financially. Various computational techniques have been proposed to predict the side effects of drugs, including methods that utilize chemical, biological, and phenotypic features. Among them, matrix factorization (MF), which harnesses the known side effects of different drugs, has shown promising results. However, methods encapsulating all characteristics of side-effect prediction have not been investigated thus far. To this effect, we employed the logistic matrix factorization (Logistic MF) algorithm, i.e., MF modified for implicit feedback data, on a spontaneous reports database to improve the accuracy of side-effect prediction.Results A weighting strategy was applied to account for differences in the importance of the drug-side effect pairs. The impact of the cold-start problem and means to tackle it using the attribute-to-feature mapping were also explored. The experimental results demonstrate that the proposed model improved the prediction accuracy by 2.3% and efficiently handled the cold-start problem.Conclusion The proposed methodology is envisaged to benefit applications such as warning systems in clinical settings.

scholarly journals Predicting the side effects of drugs using matrix factorization on spontaneous reporting database

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kohei Fukuto ◽  
Tatsuya Takagi ◽  
Yu-Shi Tian
Keyword(s):  
Side Effects ◽  
Matrix Factorization ◽  
Side Effect ◽  
Cold Start ◽  
Factorization Method ◽  
Mapping Method ◽  
Spontaneous Reports ◽  
The Matrix ◽  
History Of ◽  
Cold Start Problem

AbstractThe severe side effects of some drugs can threaten the lives of patients and financially jeopardize pharmaceutical companies. Computational methods utilizing chemical, biological, and phenotypic features have been used to address this problem by predicting the side effects. Among these methods, the matrix factorization method, which utilizes the side-effect history of different drugs, has yielded promising results. However, approaches that encapsulate all the characteristics of side-effect prediction have not been investigated to date. To address this gap, we applied the logistic matrix factorization algorithm to a database of spontaneous reports to construct a prediction with higher accuracy. We expressed the distinction in the importance of drug-side effect pairs by a weighting strategy and addressed the cold-start problem via an attribute-to-feature mapping method. Consequently, our proposed model improved the prediction accuracy by 2.5% and efficiently handled the cold-start problem. The proposed methodology is expected to benefit applications such as warning systems in clinical settings.

The Impact of Prescribed Medication on Swallowing: An Overview

2010 ◽  
Vol 19 (4) ◽  
pp. 98-102 ◽  
Author(s):  
Louise Gallagher
Keyword(s):  
Side Effects ◽  
Best Practices ◽  
Side Effect ◽  
Team Member ◽  
Assessment Process ◽  
Valuable Resource ◽  
Speech Language Pathologists ◽  
Swallowing Difficulties ◽  
The Impact

Dysphagia clinicians are aware that best practices guidelines recommend a medications review as part of the assessment process. This article aims to review the literature to date regarding the impact that medications may have on the physiology of swallowing. It is important to consider the side effects of all medications, not only medications listing swallowing difficulties as a known side effect. Medications that impact upon arousal, awareness, and xerostomia should also be considered as part of a comprehensive dysphagia evaluation. Speech-language pathologists should consider the pharmacist an integral dysphagia team member and a valuable resource.

Determining the impact of chemotherapy-induced peripheral neuropathy: A survey of cancer survivors.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e24080-e24080
Author(s):  
Eva Battaglini ◽  
David Goldstein ◽  
Susanna Park
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Peripheral Neuropathy ◽  
Side Effects ◽  
Cancer Survivors ◽  
Side Effect ◽  
Functional Disability ◽  
Health Conditions ◽  
The Impact

e24080 Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a major yet poorly understood side effect of cancer treatment, leading to symptoms including numbness, tingling and pain. It can lead to cessation of effective treatment, long-term functional disability and reduced quality of life. Despite this, there is currently little understanding of its impact. Methods: The aim of the study was to investigate the impact of neurotoxic chemotherapy side effects on the lives of cancer survivors. Data was collected via an online survey covering demographics, cancer diagnosis and treatment, CIPN and other side effects of chemotherapy, using standardised measures to assess comorbidities, quality of life, physical activity, pain and CIPN symptoms. Results: Data was analysed from 986 respondents who were treated with neurotoxic therapies (83% female, 16% male), with mean age 59 years ( SD 10.7 years). A majority of respondents were treated for breast cancer (59%), 14% for colorectal cancer and 11% for multiple myeloma. Chemotherapy types received included paclitaxel (32%), docetaxel (32%) and oxaliplatin (13%), and respondents completed treatment a mean of 3.6 years ago. The majority of respondents (80%) reported experiencing neuropathic symptoms after finishing chemotherapy, with 77% reporting current CIPN. Those with CIPN reported functional impacts, with 23% reporting moderate to severe problems with hand function and 28% reporting moderate to severe walking difficulties. CIPN was second most commonly rated as the treatment side effect having the greatest impact, following fatigue. Respondents with high levels of current CIPN symptoms had poorer quality of life, more comorbid health conditions, higher BMI and more often received multiple neurotoxic chemotherapies than those with low levels of CIPN symptoms. In addition, respondents who reported meeting government physical activity guidelines had lower CIPN and higher quality of life scores than those who did not meet the guidelines. Regression analyses investigating the association between quality of life and clinical and sociodemographic characteristics resulted in a model with comorbid health conditions, CIPN symptoms, years since treatment, age and physical activity as significant predictors of quality of life. Conclusions: These findings suggest that CIPN has a lasting impact on cancer survivors, leading to decreases in quality of life, often occurring alongside poorer general health. This impact supports the need for further research to improve assessment, prevention and treatment.

scholarly journals Impact of Pharmacist Counselling on Clozapine Knowledge

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Ciara Ní Dhubhlaing ◽  
Ailish Young ◽  
Laura J. Sahm
Keyword(s):  
Side Effects ◽  
Patient Information ◽  
Side Effect ◽  
Information Sources ◽  
Knowledge Score ◽  
University Hospital ◽  
Patient Knowledge ◽  
Specific Knowledge ◽  
The Impact ◽  
Improve Patient

Clozapine is the only antipsychotic with evidence for efficacy in treatment of resistant schizophrenia but it carries a high side effect burden. Patient information is provided but may be poorly retained. This study aims to examine the impact of pharmacist counselling upon patient knowledge of clozapine. Outpatients, aged 18 years and over, attending St. Patrick’s University Hospital, Dublin, participated in this study between June and August 2015. The intervention consisted of pharmacist counselling on two occasions one month apart. Knowledge was assessed using a 28-point checklist devised from the currently available clozapine patient information sources, at baseline and after each counselling session. Ethics approval was obtained. Twenty-five participants (40% female; mean age 45.1 years, SD 9.82; 64% unemployed, 28% smokers) showed an improvement in knowledge scores of clozapine from baseline to postcounselling on each occasion with an overall improvement in knowledge score, from baseline to postcounselling at one month, of 39.43%; p<0.001. This study adds to the evidence that interventions involving pharmacist counselling can improve patient knowledge, whilst the specific knowledge gained relating to recognition of side effects may help patients towards more empowerment regarding their treatment.

scholarly journals Job change and self-control of waste pickers: evidence from a field experiment in the Philippines

2018 ◽  
Vol 9 (2) ◽  
pp. 22-35
Author(s):  
Hide-Fumi Yokoo ◽  
Maki Ikuse ◽  
Aries Roda D. Romallosa ◽  
Masahide Horita
Keyword(s):  
Developing Countries ◽  
Side Effects ◽  
Field Experiment ◽  
Side Effect ◽  
The Philippines ◽  
Self Control ◽  
Informal Workers ◽  
Negative Side ◽  
The Impact ◽  
Waste Pickers

Environmental policies may have a negative side effect on employment, often in a specific industry in the short run. Workers in regulated industries can be affected by losses in job-specific human capital. The informal sectors in developing countries are often associated with environmental pollution and thus targeted by such policies. Welfare loss due to this side effect can be problematic in developing countries, since they often lack safeguarding schemes, including unemployment insurance. Inducing workers in informal sectors to change their jobs can mitigate these negative side effects. This study examines efficient methods of inducing informal workers to change jobs. An alternative job is offered to informal workers at a dumpsite in the Philippines and whether changing the scheme of wage payment increases the acceptance of the offer is examined. The impacts of changing payment schemes are evaluated by using a randomized field experiment. The sampled 112 waste pickers each randomly receive one of four offers for an alternative job, and the number of those who accept the offer is observed to evaluate the impact of less frequent payment (i.e., once every three days instead of daily). Piece rates and fixed wages are also compared. Those offered less frequent payment are more likely to accept the job offer compared with those offered daily payment. This preferred payment scheme can mitigate the side effects of environmental policy and workers’ self-control problem related to savings, while minimizing moral hazard.

scholarly journals ANTIRETROVIRAL SIDE EFFECT ON ADHERENCE IN PEOPLE LIVING WITH HIV AIDS AT DR. KARIADI GENERAL REFFERAL HOSPITAL SEMARANG CENTRAL JAVA

2019 ◽  
Vol 8 (2) ◽  
pp. 79 ◽  
Author(s):  
Gede Arya Bagus Arisudhana ◽  
Muchlis Achsan Udji Sofro ◽  
Untung Sujianto
Keyword(s):  
Health Care ◽  
Side Effects ◽  
Side Effect ◽  
People Living With Hiv ◽  
Drug Adherence ◽  
Cross Sectional ◽  
Central Java ◽  
Living With Hiv ◽  
The Impact ◽  
Hiv Aids

Background: Antiretroviral (ARV) therapy is a lifelong treatment in people living with HIV/AIDS (PLWHA). Adherence is the key to the effectiveness of antiretroviral therapy. ARV have side effects that may affect patient adherence.Purpose: The purpose of this study was to examine the impact of ARV side effects on drug adherence in PLWHA.Methods: This study used cross-sectional approach. Sample size in this study was 78 consist of people who were recruited by purposive sampling. These subjects received ARV therapy in Tropical Disease and Infection Polyclinic at General Hospital of Dr. Kariadi SemarangResult : Result showed that eta2 is 0,525625. It means that ARV side effect has impact on ARV adherence. Most of the side effects reported by the respondents were nausea and dizziness. Some respondents also reported experiencing weakness, difficult to concentrate, and diarrhea. Conclusion : Side effects have impact on patient’s ARV therapy adherence. Therefore health care provider for PLWHA should be able to recognize and concern on ARV side effect management. 

scholarly journals A Novel Triple Matrix Factorization Method for Detecting Drug-Side Effect Association Based on Kernel Target Alignment

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiaoyi Guo ◽  
Wei Zhou ◽  
Yan Yu ◽  
Yijie Ding ◽  
Jijun Tang ◽  
...  
Keyword(s):  
Side Effects ◽  
Matrix Factorization ◽  
Side Effect ◽  
Multiple Kernel Learning ◽  
Factorization Method ◽  
Low Rank ◽  
Low Rank Approximation ◽  
Original Matrix ◽  
Multiple Kernel ◽  
Benchmark Datasets

All drugs usually have side effects, which endanger the health of patients. To identify potential side effects of drugs, biological and pharmacological experiments are done but are expensive and time-consuming. So, computation-based methods have been developed to accurately and quickly predict side effects. To predict potential associations between drugs and side effects, we propose a novel method called the Triple Matrix Factorization- (TMF-) based model. TMF is built by the biprojection matrix and latent feature of kernels, which is based on Low Rank Approximation (LRA). LRA could construct a lower rank matrix to approximate the original matrix, which not only retains the characteristics of the original matrix but also reduces the storage space and computational complexity of the data. To fuse multivariate information, multiple kernel matrices are constructed and integrated via Kernel Target Alignment-based Multiple Kernel Learning (KTA-MKL) in drug and side effect space, respectively. Compared with other methods, our model achieves better performance on three benchmark datasets. The values of the Area Under the Precision-Recall curve (AUPR) are 0.677, 0.685, and 0.680 on three datasets, respectively.

Multilevel term analysis for adaptive document filtering1

2020 ◽  
Vol 24 ◽  
pp. 3-14
Author(s):  
Adrian Fonseca Bruzón ◽  
Aurelio López-López ◽  
José E. Medina Pagola
Keyword(s):  
Information Needs ◽  
User Profile ◽  
Cold Start ◽  
Semantic Content ◽  
Textual Structure ◽  
Document Filtering ◽  
The Impact ◽  
Term Analysis ◽  
Cold Start Problem

Humans tend to organize information in documents in a logical and intentional way. This organization, which we call textual structure, is commonly in terms of sections, chapters, paragraphs, or sentences. This structure facilitates the understanding of the content that we want to transmit to the readers. However, such structure, in which we usually encode the semantic content of information, is not usually exploited by the filtering methods for the construction of a user profile. In this work, we propose the use of term relations considering different context levels for enhancing document filtering. We propose methods for obtaining the representation, considering the existence of imbalance between the documents that satisfy the information needs of users, as well as the Cold Start problem (having scarce information) during the initial construction of the user profile. The experiments carried out allowed to assess the impact, in terms of T11SU measure, on the filtering task of the proposed representation.

Sign in / Sign up

Export Citation Format

Share Document