Croatia’s research while affiliated with University of Rijeka and other places

The development of rural tourism in Azerbaijan is one of the priority and promising areas of the economy. Our country has a wide potential for the development of rural tourism. The presence of settlements distinguished by favorable natural conditions, exotic landscapes and ethnography creates ample opportunities for the development of rural tourism. The development of the tourism economy in rural areas is of extraordinary socio-economic importance. The development of this type of tourism leads to the creation of a permanent and year-round additional income source in the countryside and the creation of new workplaces in the villages. The development of rural tourism has an important role in obtaining new markets for the sale of products produced by the rural population and in developing the local service culture. The population engaged in this type of tourism has the opportunity to earn income from the sale of handmade products, local and traditional dishes, the food products necessary for their cooking, and tourist transportation. Currently, important studies are carried out at the state level in order to accelerate the development of tourism in our republic and to attract the attention of foreign tourists to the beautiful corners of the country. In recent years, many decrees and instructions that serve the development of tourism have been issued. The article evaluates the impact of rural tourism on socio-economic development. Also are researched the development possibilities and current situation of rural tourism and suggestions are made for the solution of the emerging problems in Azerbaijan.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.

It has been recognized that chronic renal impairment can modify the level of the global CV risk. This fact is of the great importance for planning prevention of CV disease, since mild-moderate chronic renal impairment occurs in an adult population with high frequency of 5%-10%. While clinical and biochemical disorders which can contribute to high CV risk of patients with end-stage-renal-disease are well known, these disorders in people with early stages of chronic renal impairment are poorly defined. In order to better clarify this issue, we presented here a predictive approach where data mining algorithms were performed and evaluated on a dataset composed of a large number of clinical parameters,which describe the health status of older subjects, primary healthcare (PHC) attenders, burdened with multiple medical conditions and CV risk factors. Results were compared with evidence on CV risk factors in end-stage-renal-disease.