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J M DeLeo

Publications and source records attributed to J M DeLeo.

8 recordsLinked to original sources
PubMed1996

What can artificial neural networks teach us about neurodegenerative disorders with extrapyramidal features?

Artificial neural networks (ANNs), computer paradigms that can learn, excel in pattern recognition tasks such as disease diagnosis. Artificial neural networks operate in two different learning modes: supervised, in which a known diagnostic outcome is presented to the ANN, and unsupervised, in which the diagnostic outcome is not presented. A supervised learning ANN could emulate human expert diagnostic performance and identify relevant predictive markers in the diagnostic task, while an unsupervised learning ANN could suggest reasonable alternative diagnostic classification criteria. In the present study, we used ANN methodology to try to overcome the neuropathological difficulties in differentiating the subtypes of progressive supranuclear palsy (PSP), and in differentiating PSP from postencephalitic parkinsonism (PEP) and corticobasal degeneration, or Pick's disease from corticobasal degeneration. First, we applied supervised learning ANN to classify 62 cases of these disorders and to identify diagnostic markers that distinguish them. In a second experiment, we used unsupervised learning ANN to investigate possible alternative nosological classifications. Artificial neural networks input data for each case consisted of values representing histological features, including neurofibrillary tangles, neuronal loss and gliosis found in multiple brain sampling areas. The supervised learning ANN achieved excellent accuracy in classifying PSP but had difficulty classifying the other disorders. This method identified a few features that might help to differentiate PEP, supported currently proposed criteria for Pick's disease, corticobasal degeneration and typical PSP, but detected no features to characterize the atypical subtype of PSP. In general, unsupervised learning ANN supported the present nosological classification for PSP, PEP, Pick's disease and corticobasal degeneration, although it overlapped some groups. Artificial neural networks methodology appears promising for studying neurodegenerative disorders.

Basal Ganglia Diseases↗
PubMed1995

Pleural fluid chemical analysis in parapneumonic effusions. A meta-analysis.

Controversy exists regarding the clinical utility of pleural fluid pH, lactate dehydrogenase (LDH), and glucose for identifying complicated parapneumonic effusions that require drainage. In this report, we performed a meta-analysis of pertinent studies, using receiver operating characteristic (ROC) techniques, to assess the diagnostic accuracy of these tests, to determine appropriate decision thresholds, and to evaluate the quality of the primary studies. Seven primary studies reporting values for pleural fluid pH (n = 251), LDH (n = 114), or glucose (n = 135) in pneumonia patients were identified. We found that pleural fluid pH had the highest diagnostic accuracy for all patients with parapneumonic effusions as measured by the area under the ROC curve (AUC = 0.92) compared with pleural fluid glucose (AUC = 0.84) or LDH (AUC = 0.82). After excluding patients with purulent effusions, pH (AUC = 0.89) retained the highest diagnostic accuracy. Pleural fluid pH decision thresholds varied between 7.21 and 7.29 depending on cost-prevalence considerations. The quality of the primary studies was the major limitation in determining the value of pleural fluid chemical analysis. We conclude that meta-analysis of the available data refines the application of pleural fluid chemical analysis but a clearer understanding of the usefulness of these tests awaits more rigorous primary investigations.

Chest Tubes↗
PubMed1993

Patient-interactive computer system for obtaining medication histories.

A portable, patient-interactive computerized system for obtaining medication histories is described. A comprehensive interview script modeling pharmacist-conducted medication-history interviews was written in lay language. The script contains sections on demographics, current medical conditions, medication regimen, medication compliance, symptoms, allergy history, dietary history, psychosocial history, and occupational and environmental exposure; it also asks the patient to evaluate the system. Some of the information requested is often not obtained by physicians during the history and physical examination. A program that conducts the interview by processing a computerized version of the script was developed with Microsoft QuickBASIC. The program was designed to be run on a personal computer microprocessor so that an interview can be conducted virtually anywhere by using a desktop or laptop computer. Summary reports suitable for inclusion in the medical record are generated after each interview. Patients using the system took an average of 40 minutes to complete an interview. They entered data easily and accurately, and they gave the system a high overall rating. The medication-history interviewing system described produces useful, comprehensive, and consistent reports and requires about the same amount of time to conduct an interview as a human interviewer.

Adult↗
PubMed1985

Computed tomographic analysis of brain morphometrics in 30 healthy men, aged 21 to 81 years.

Computed transverse axial tomography (CT) was employed to examine brain morphometrics in 30 healthy men, aged 21 to 81 years. Seven consecutive CT slices 30 to 80 mm above the inferior orbitomeatal line were analyzed. CT numbers in gray and white matter regions were not correlated significantly with age (p greater than 0.05), nor were right/left ratios for derived parameters. The volume of gray matter was correlated negatively with age (p less than 0.05), and the volume of cerebrospinal fluid correlated positively with age, in the seven slices. The volumes of the lateral and third ventricles were elevated in the elderly, and volumes of the thalamus and lenticular nucleus were reduced. The results demonstrate that brain atrophy, evidenced by a loss of gray matter and by dilatation of cerebrospinal fluid spaces, occurs in the healthy elderly, and provide baseline CT-derived brain morphometric data for healthy men in relation to age.

Adult↗
PubMed1985

Computer-assisted categorization of brain computerized tomography pixels into cerebrospinal fluid, white matter, and gray matter.

A computer-assisted method was employed to estimate the amounts of cerebrospinal fluid (CSF), white matter, and gray matter in individual computerized tomography (CT) scans of brains. By means of an image processing procedure (DMORPH), the means +/- SD CT numbers of "pure" CSF, white matter, and gray matter were determined in each scan and stored. A CATSEG program used these means to define ranges for CT numbers for each of the three tissues on each scan, and to assign each pixel in a scan to one of the three categories. Summing over seven serial scans provided volumetric estimates of CSF, white matter, and gray matter in a brain segment. For 10 subjects aged 21 to 43 years, CSF volume equaled 1.4 to 4.7% of the total segment volume, white matter equaled 37.5 to 48.2%, and gray matter equaled 50.2 to 58.9%. Image processing hardware and software which allow standardized sampling from CT images for the evaluation of surface areas and CT numbers are described. These procedures, as applied to CT scans of the human brain, can be used to estimate the volumes of CSF, white matter, and gray matter in a selected intracranial segment.

Brain↗
PubMed1983

Sequential comparative hybridizations analyzed by computerized image processing can identify and quantitate regulated RNAs.

A method to analyze shifts in the relative abundance of many specific RNAs following any stimulus is presented. Hybridizations of two complex "total" cDNA probes (from the pre- and poststimulus states) to each member of a cDNA library are quantitatively analyzed and mathematically compared by using computer-assisted image processing and statistical analysis of sequential filter hybridizations. Experiments indicate that shifts in abundance between two states can be identified and reproducibly quantitated without purified probes. Direct isolation of recombinant cDNA colonies containing inserts corresponding to regulated RNAs is thus possible. The use of this system is demonstrated for partial analysis of the response in vivo of rat liver to glucocorticoids. Application to other biological systems in which a shift between two states occurs is discussed.

Animals↗
PubMedDate not supplied

Development of a questionnaire for detecting potential adverse drug reactions.

OBJECTIVE: To develop a comprehensive list of symptoms categorized by body system as part of a questionnaire for detecting potential adverse drug reactions. DATA SOURCES: A preliminary list of symptoms in lay terminology was extracted from the "Side Effects" section of all drug monographs contained in the United States Pharmacopeia Dispensing Information (USP DI) computerized database (Volume II, Advice for the Patient) using natural language processing software. The list was sorted alphabetically and duplicate terms were eliminated. Symptoms were then categorized by body system or anatomic region. A preferred term for each symptom was selected when multiple synonyms and related words were listed. Finally, all of the symptom terms were incorporated into a thesaurus from which the questionnaire was derived. RESULTS: The questionnaire will be used as part of a computer-assisted interview, developed to solicit information from patients regarding their medication regimens and to systematically query them regarding the presence of salient symptoms or complaints. The computer system will eventually interface with the USP DI database to identify drugs from a patient's regimen that may be associated with adverse symptoms. The symptom thesaurus will provide the link to the USP DI database. Preliminary experience with the questionnaire in a limited number of patients has been encouraging. CONCLUSIONS: The questionnaire can assist clinicians in identifying drug-related symptoms including unreported adverse clinical effects of newly marketed or investigational therapeutic agents. When the questionnaire is computerized and linked to a comprehensive database, it can be more widely used to alert healthcare providers of potential adverse drug reactions that may otherwise go undetected.

Adverse Drug Reaction Reporting Systems↗