Biomedical subjects

Rajan Patel

Publications and source records attributed to Rajan Patel.

4 recordsLinked to original sources

PubMed2004

Methods for detecting functional classifications in neuroimaging data.

Data-driven statistical methods are useful for examining the spatial organization of human brain function. Cluster analysis is one approach that aims to identify spatial classifications of temporal brain activity profiles. Numerous clustering algorithms are available, and no one method is optimal for all areas of application because an algorithm's performance depends on specific characteristics of the data. K-means and fuzzy clustering are popular for neuroimaging analyses, and select hierarchical procedures also appear in the literature. It is unclear which clustering methods perform best for neuroimaging data. We conduct a simulation study, based on PET neuroimaging data, to evaluate the performances of several clustering algorithms, including a new procedure that builds on the kth nearest neighbor method. We also examine three stopping rules that assist in determining the optimal number of clusters. Five hierarchical clustering algorithms perform best in our study, some of which are new to neuroimaging analyses, with Ward's and the beta-flexible methods exhibiting the strongest performances. Furthermore, Ward's and the beta-flexible methods yield the best performances for noisy data, and the popular K-means and fuzzy clustering procedures also perform reasonably well. The stopping rules also exhibit good performances for the top five clustering algorithms, and the pseudo-T2 and pseudo-F stopping rules are superior for noisy data. Based on our simulations for both noisy and unscaled PET neuroimaging data, we recommend the combined use of the pseudo-F or pseudo-T2 stopping rule along with either Ward's or the beta-flexible clustering algorithm.

Algorithms↗

PubMed2004

Identifying spatial relationships in neural processing using a multiple classification approach.

The application of statistical classification methods to in vivo functional neuroimaging data makes it possible to explore spatial patterns in task-related changes in neural processing. Cluster analysis is one group of descriptive statistical procedures that can assist in identifying classes of brain regions that exhibit similar task-related functionality. In practice, a limitation of cluster analysis is that the performances of clustering algorithms rely on unknown characteristics of the data, making it difficult to determine which procedure best suits a particular analysis. We present a multiple classification approach that incorporates numerous algorithms, evaluates the associated classifications, and either selects a plausible partition relative to the others considered or pools the results from the numerous methods. The multiple classification approach utilizes a new performance criterion, called the relative information (RI) measure, to evaluate the quality of the candidate partitions and as the basis for producing a composite classification image. Employing multiple classifications, rather than a single algorithm, our methodology increases the chance of detecting the functional relationships within the data and, therefore, produces more reliable results. We apply our methodology to a PET study to explore spatial relationships in measured brain function associated with increasing blood alcohol concentration levels, and we perform a simulation study to evaluate the performance of RI.

Alcoholic Intoxication↗

PubMed2004

Atrial fibrillation in a multiethnic inpatient population of a large public hospital.

INTRODUCTION: Atrial fibrillation (AF) has not been well-studied in minority and underserved populations. We report a one-year inpatient experience of AF among 80,021 total ECG records in a multiethnic population of a large public hospital. METHODS: ECG parameters, demographic data, discharge diagnoses, and discharge status were compiled for the first 1,999 hospitalizations associated with AF among 80,021 total ECG records and compared among the population subgroups. RESULTS: Of 3,935 records of patients with AF, 737 matched first hospitalizations. Mean age was 62.3 years; 56% were male. Hispanics comprised 59.2%, Caucasians 16.4%, Asians 11.1%, African Americans 10.3%; unclassified 3%; 30.6% were uninsured. Compared to Caucasians, Left ventricular hypertrophy was more common in African-American [9.9% vs. 21.1%, odds ratio (OR)=2.3] and Asians (9.9% vs. 15.3%, OR=2.76). At discharge, Caucasians more frequently had coronary artery disease, compared to Hispanics (26.4% vs. 17.7%, OR=0.62), African Americans (26.4% vs. 10.5%, OR=0.36), and Asians (26.4% vs. 8.5%, OR=0.25); cardiomyopathy was less common in Caucasians as compared to African Americans (2.5% vs. 10.5%, OR=4.2), Hispanics (2.5% vs. 3.9%, OR=1.5) and Asians (2.5% vs. 4.9%, OR=1.96). Mortality was 16%; nonsurvivors compared to survivors were older, 64.9 years vs. 61.8 years, p<0.05, more frequently had myocardial infarction (20.4% vs. 6.2%, p=0.000) and stroke (16.5% vs. 5.0%, p=0.000). CONCLUSIONS: This AF population, particularly African Americans, was younger than previously reported. ECG and discharge parameters had differential frequencies among race/ethnic subgroups. Nonsurvivors were older and more commonly had myocardial infarction and stroke. Further study is warranted of AF occurrence, management, and outcomes in lower-socioeconomic, multiethnic populations.

Adult↗

PubMed2002

Evaluating the organizational effectiveness of APC implementation efforts.

To optimize revenue under the Medicare outpatient prospective payment system's new coding-based ambulatory payment classifications (APCs), healthcare providers need to ensure several key steps are taken at the organizational level. Individuals who manage coding need to identify areas of overlap and adjust billing systems to reflect changes under the system. Billing managers should develop practices and protocols that provide detailed reviews of claims, implement a formal denial management program, track reasons for denials, and communicate denial information with their staffs. Proper evaluation of financial practices also is important. Financial managers need to develop formal ways to monitor financial performance consistently and on an ongoing basis and ensure the hospital is generating sufficient volume and keeping service costs in line with payments.

Abstracting and Indexing↗