Multilabel classification of unstructured data using Crunchbase

Our work compares different methods and models for multilabel text classification using information collected from Crunchbase, a large database that holds information of more than 600000 companies. Each company is labeled with one more categories, from a subset of 46 possible, and the proposed models predict the categories based solely on the company textual description. A number of natural language processing strategies have been tested for feature extraction, including stemming, lemmatization, and Part-of-Speech Tagging. This is a highly unbalanced dataset, where the frequency of each category ranges from 0.7% to 28%. The first experiment, is a Multiclass classification problem that tries to find the most probable category using only one model for all categories, with an overall score of 67% using SVM, Naive Bayes and Fuzzy Fingerprints. The second experiment uses makes use of multiple classifiers, one for each category, and tries to predict the complete set of categories for each company, with an overal score of 73% precision and 47% recall. The resulting models may constitute an important asset for automatic classification of texts, not only consisting of company descriptions, but also other texts, such as web pages, text blogs, news pages, etc.Este trabalho compara diferentes métodos e modelos para classificação de texto utilizando informação proveniente do Crunchbase, uma grande base de dados que contém dados sobre mais de 600000 empresas. Cada empresa está associada a uma ou mais categorias, de 46 possiveis, e os modelos propostos utilizam apenas a descrição de cada empresa para prever a sua categoria. Foram aplicadas várias técnicas de processamento de linguagem natural para extração de informação incluindo "stemming", lematização e "Part-of-Speech Tagging". Este "dataset" é altamente desiquilibrado, a frequência de cada categoria vai desde 0.7% a 28%. A primeira experiência, é um problema multiclasse que tenta encontrar qual a categoria mais provável para uma empresa utilizando apenas um modelo para todas as categorias, obtendo um resultado global de 67% de "accuracy" utilizando SVM, Naive Bayes e Fuzzy Fingerprints. A segunda experiência utiliza vários classificadores, um por cada categoria, para atribuir todas as categorias de uma determinada empresa obtendo resultados de 73% de precisão e 47% de "recall". Os modelos resultantes do nosso trabalho podem ser um ativo importante para a classificação automática de texto, não só para descrições de empresas mas também para outros textos, como páginas de Internet, blogs, notícias, entre outros

Creating classification models from textual descriptions of companies using crunchbase

This paper compares different models for multilabel text classification, using information collected from Crunchbase, a large database that holds information about more than 600000 companies. Each company is labeled with one or more categories, from a subset of 46 possible categories, and the proposed models predict the categories based solely on the company textual description. A number of natural language processing strategies have been tested for feature extraction, including stemming, lemmatization, and part-of-speech tags. This is a highly unbalanced dataset, where the frequency of each category ranges from 0.7% to 28%. Our findings reveal that the description text of each company contain features that allow to predict its area of activity, expressed by its corresponding categories, with about 70% precision, and 42% recall. In a second set of experiments, a multiclass problem that attempts to find the most probable category, we obtained about 67% accuracy using SVM and Fuzzy Fingerprints. The resulting models may constitute an important asset for automatic classification of texts, not only consisting of company descriptions, but also other texts, such as web pages, text blogs, news pages, etc.info:eu-repo/semantics/publishedVersio

Processo analítico hierárquico na identificação de áreas favoráveis ao agroecossistema cafeeiro em escala municipal Analytical hierarchical process to identify favorable areas to the coffee crop agroecosystem at municipal scale

O objetivo deste trabalho foi delimitar áreas favoráveis ao agroecossistema cafeeiro, em quatro municípios do Estado de Minas Gerais, pela aplicação do processo analítico hierárquico (AHP). Uma função de ponderação aritmética foi obtida, com base nas premissas de favorabilidade à cafeicultura, considerando-se as seguintes variáveis: solo, declividade, orientação de vertentes, altimetria e as possíveis áreas de preservação permanente. Essa função permitiu combinar as condições adequadas ao cultivo do café e ressaltar as áreas com maior favorabilidade. Foi verificado que os quatro municípios diferem entre si quanto à favorabilidade ao agroecossistema cafeeiro; porém, ao se considerar apenas as áreas cultivadas com café, foi verificado que os municípios de Boa Esperança e Cristais não diferem entre si.<br>The objective of this work was to delimitate favorable areas to the coffee agroecosystem, in four municipalities of Minas Gerais State, Brazil, using the analytical hierarchical process (AHP). An arithmetic pondering function was obtained, based on the favorability premises to coffee crop production, with regard to the following variables: soil, slope, slope aspect, altimetry, and areas that should be under permanent protection. This function allowed to combine the adequate conditions to coffee crop cultivation and gave emphasis to the most favorable areas. It was observed that all four municipalities were different in terms of their favorability to the coffee agroecosystem; however, when considering only the coffee cultivated areas, it was observed that the municipalities of Boa Esperança and Cristais were not significantly different

Sparsentan in patients with IgA nephropathy: a prespecified interim analysis from a randomised, double-blind, active-controlled clinical trial

Background: Sparsentan is a novel, non-immunosuppressive, single-molecule, dual endothelin and angiotensin receptor antagonist being examined in an ongoing phase 3 trial in adults with IgA nephropathy. We report the prespecified interim analysis of the primary proteinuria efficacy endpoint, and safety. Methods: PROTECT is an international, randomised, double-blind, active-controlled study, being conducted in 134 clinical practice sites in 18 countries. The study examines sparsentan versus irbesartan in adults (aged ≥18 years) with biopsy-proven IgA nephropathy and proteinuria of 1·0 g/day or higher despite maximised renin-angiotensin system inhibitor treatment for at least 12 weeks. Participants were randomly assigned in a 1:1 ratio to receive sparsentan 400 mg once daily or irbesartan 300 mg once daily, stratified by estimated glomerular filtration rate at screening (30 to 1·75 g/day). The primary efficacy endpoint was change from baseline to week 36 in urine protein-creatinine ratio based on a 24-h urine sample, assessed using mixed model repeated measures. Treatment-emergent adverse events (TEAEs) were safety endpoints. All endpoints were examined in all participants who received at least one dose of randomised treatment. The study is ongoing and is registered with ClinicalTrials.gov, NCT03762850. Findings: Between Dec 20, 2018, and May 26, 2021, 404 participants were randomly assigned to sparsentan (n=202) or irbesartan (n=202) and received treatment. At week 36, the geometric least squares mean percent change from baseline in urine protein-creatinine ratio was statistically significantly greater in the sparsentan group (-49·8%) than the irbesartan group (-15·1%), resulting in a between-group relative reduction of 41% (least squares mean ratio=0·59; 95% CI 0·51-0·69; p<0·0001). TEAEs with sparsentan were similar to irbesartan. There were no cases of severe oedema, heart failure, hepatotoxicity, or oedema-related discontinuations. Bodyweight changes from baseline were not different between the sparsentan and irbesartan groups. Interpretation: Once-daily treatment with sparsentan produced meaningful reduction in proteinuria compared with irbesartan in adults with IgA nephropathy. Safety of sparsentan was similar to irbesartan. Future analyses after completion of the 2-year double-blind period will show whether these beneficial effects translate into a long-term nephroprotective potential of sparsentan. Funding: Travere Therapeutics

Sparsentan in patients with IgA nephropathy: a prespecified interim analysis from a randomised, double-blind, active-controlled clinical trial

Background: Sparsentan is a novel, non-immunosuppressive, single-molecule, dual endothelin and angiotensin receptor antagonist being examined in an ongoing phase 3 trial in adults with IgA nephropathy. We report the prespecified interim analysis of the primary proteinuria efficacy endpoint, and safety. Methods: PROTECT is an international, randomised, double-blind, active-controlled study, being conducted in 134 clinical practice sites in 18 countries. The study examines sparsentan versus irbesartan in adults (aged ≥18 years) with biopsy-proven IgA nephropathy and proteinuria of 1·0 g/day or higher despite maximised renin-angiotensin system inhibitor treatment for at least 12 weeks. Participants were randomly assigned in a 1:1 ratio to receive sparsentan 400 mg once daily or irbesartan 300 mg once daily, stratified by estimated glomerular filtration rate at screening (30 to &lt;60 mL/min per 1·73 m2 and ≥60 mL/min per 1·73 m2) and urine protein excretion at screening (≤1·75 g/day and &gt;1·75 g/day). The primary efficacy endpoint was change from baseline to week 36 in urine protein–creatinine ratio based on a 24-h urine sample, assessed using mixed model repeated measures. Treatment-emergent adverse events (TEAEs) were safety endpoints. All endpoints were examined in all participants who received at least one dose of randomised treatment. The study is ongoing and is registered with ClinicalTrials.gov, NCT03762850. Findings: Between Dec 20, 2018, and May 26, 2021, 404 participants were randomly assigned to sparsentan (n=202) or irbesartan (n=202) and received treatment. At week 36, the geometric least squares mean percent change from baseline in urine protein–creatinine ratio was statistically significantly greater in the sparsentan group (–49·8%) than the irbesartan group (–15·1%), resulting in a between-group relative reduction of 41% (least squares mean ratio=0·59; 95% CI 0·51–0·69; p&lt;0·0001). TEAEs with sparsentan were similar to irbesartan. There were no cases of severe oedema, heart failure, hepatotoxicity, or oedema-related discontinuations. Bodyweight changes from baseline were not different between the sparsentan and irbesartan groups. Interpretation: Once-daily treatment with sparsentan produced meaningful reduction in proteinuria compared with irbesartan in adults with IgA nephropathy. Safety of sparsentan was similar to irbesartan. Future analyses after completion of the 2-year double-blind period will show whether these beneficial effects translate into a long-term nephroprotective potential of sparsentan. Funding: Travere Therapeutics

Efficacy and safety of sparsentan versus irbesartan in patients with IgA nephropathy (PROTECT): 2-year results from a randomised, active-controlled, phase 3 trial

Background Sparsentan, a novel, non-immunosuppressive, single-molecule, dual endothelin angiotensin receptor antagonist, significantly reduced proteinuria versus irbesartan, an angiotensin II receptor blocker, at 36 weeks (primary endpoint) in patients with immunoglobulin A nephropathy in the phase 3 PROTECT trial's previously reported interim analysis. Here, we report kidney function and outcomes over 110 weeks from the double-blind final analysis. Methods PROTECT, a double-blind, randomised, active-controlled, phase 3 study, was done across 134 clinical practice sites in 18 countries throughout the Americas, Asia, and Europe. Patients aged 18 years or older with biopsy-proven primary IgA nephropathy and proteinuria of at least 1·0 g per day despite maximised renin–angiotensin system inhibition for at least 12 weeks were randomly assigned (1:1) to receive sparsentan (target dose 400 mg oral sparsentan once daily) or irbesartan (target dose 300 mg oral irbesartan once daily) based on a permuted-block randomisation method. The primary endpoint was proteinuria change between treatment groups at 36 weeks. Secondary endpoints included rate of change (slope) of the estimated glomerular filtration rate (eGFR), changes in proteinuria, a composite of kidney failure (confirmed 40% eGFR reduction, end-stage kidney disease, or all-cause mortality), and safety and tolerability up to 110 weeks from randomisation. Secondary efficacy outcomes were assessed in the full analysis set and safety was assessed in the safety set, both of which were defined as all patients who were randomly assigned and received at least one dose of randomly assigned study drug. This trial is registered with ClinicalTrials.gov, NCT03762850. Findings Between Dec 20, 2018, and May 26, 2021, 203 patients were randomly assigned to the sparsentan group and 203 to the irbesartan group. One patient from each group did not receive the study drug and was excluded from the efficacy and safety analyses (282 [70%] of 404 included patients were male and 272 [67%] were White) . Patients in the sparsentan group had a slower rate of eGFR decline than those in the irbesartan group. eGFR chronic 2-year slope (weeks 6–110) was −2·7 mL/min per 1·73 m2 per year versus −3·8 mL/min per 1·73 m2 per year (difference 1·1 mL/min per 1·73 m2 per year, 95% CI 0·1 to 2·1; p=0·037); total 2-year slope (day 1–week 110) was −2·9 mL/min per 1·73 m2 per year versus −3·9 mL/min per 1·73 m2 per year (difference 1·0 mL/min per 1·73 m2 per year, 95% CI −0·03 to 1·94; p=0·058). The significant reduction in proteinuria at 36 weeks with sparsentan was maintained throughout the study period; at 110 weeks, proteinuria, as determined by the change from baseline in urine protein-to-creatinine ratio, was 40% lower in the sparsentan group than in the irbesartan group (−42·8%, 95% CI −49·8 to −35·0, with sparsentan versus −4·4%, −15·8 to 8·7, with irbesartan; geometric least-squares mean ratio 0·60, 95% CI 0·50 to 0·72). The composite kidney failure endpoint was reached by 18 (9%) of 202 patients in the sparsentan group versus 26 (13%) of 202 patients in the irbesartan group (relative risk 0·7, 95% CI 0·4 to 1·2). Treatment-emergent adverse events were well balanced between sparsentan and irbesartan, with no new safety signals. Interpretation Over 110 weeks, treatment with sparsentan versus maximally titrated irbesartan in patients with IgA nephropathy resulted in significant reductions in proteinuria and preservation of kidney function.</p