A Novel Mathematical Approach to Diagnose Premenstrual Syndrome

Chattopadhyay, Subhagata; Acharya, U. Rajendra

doi:10.1007/s10916-011-9683-4

Cited by 16 publications

(7 citation statements)

References 22 publications

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“…The results of the study revealed that 90.5% of the participants suffer from PMS, ranging from moderate to very severe, and 87.2% had dysmenorrhea. The worldwide prevalence of PMS was estimated between 5-76% [17][18] , while the present findings showed higher values. The prevelance of dysmenorrhea in the current study is supported in the literature with similar percentages 17,19,20 There was a positive correlation between PSQI and PMS in both total score and sub scores.…”

Section: Discussioncontrasting

confidence: 48%

The relationship between premenstrual syndrome and the quality of sleep among Egyptian women: an observational study

Kamel¹,

Tantawy²,

LSAYED³

et al. 2021

Arch Balk Med Union

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La relation entre le syndrome prémenstruel et la qualité du sommeil chez les femmes égyptiennes: une étude observationnelleIntroduction. Le syndrome prémenstruel (SPM) est un désordre comprenant des symptômes physiques, psychologiques et comportementaux. Ensemble, ces symptômes peuvent affecter la qualité de vie des femmes sous différents aspects. L'objectif de l'étude était d'étudier la relation entre le syndrome prémenstruel (SPM) et la qualité du sommeil chez les femmes en âge de procréer. Matériel et méthodes. L'étude est transversale, avec un échantillon de 768 femmes en âge de procréer qui ont répondu à un questionnaire autodéclaré. Ce questionnaire compilé comprenait trois parties de la fiche de données démographiques, l'échelle du syndrome prémenstruel (PMSS) et l'indice de qualité du sommeil ABSTRACT Introduction. Premenstrual syndrome (PMS) is a disorder characterized by physical, psychological and behavioural symptoms. These symptoms can affect the women's quality of life on different aspects. The objective of the study was to investigate the relationship between PMS and sleep quality among women of reproductive age. Materials and methods. This is a cross sectional study on 768 women of reproductive age, who answered a self-reported questionnaire. This questionnaire consisted of three parts: demographic data sheet, premenstrual syndrome scale (PMSS) and Pittsburg Sleep Quality Index (PSQI). The primary outcome was the prevalence and severity of PMS and sleep quality, in addition to the correlation between PMS and PSQI. The demographic characteristics of participants and their impact on the PMS and PSQI were secondary outcomes.

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Section: Discussioncontrasting

confidence: 48%

The relationship between premenstrual syndrome and the quality of sleep among Egyptian women: an observational study

Kamel¹,

Tantawy²,

LSAYED³

et al. 2021

Arch Balk Med Union

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“…In neuropsychiatry, such techniques have mostly been used to examine brain images and correlating images with the symptoms for diagnostic as well as prognostic purposes (Zhou et al, 2009;Kannana et al, 2010;Wismüller, 2011). Only a handful of attempts have been made to cluster clinical data (Chattopadhyay and Acharya 2011;Chattopadhyay and Daneshgar, 2011;Chattopadhyay et al, 2011a;Chattopadhyay et al, 2011b). The reasons could be (a) high levels of complexities associated within the mental health clinical data (e.g., signssymptoms are much subjective in nature) and (b) lack of multidisciplinary expertise to interpret the results.…”

Section: Applications Of Fcm and Fknn In Neuropsychiatry: A Brief Reviewmentioning

confidence: 99%

Mathematical modelling of doctors' perceptions in the diagnosis of depression: a novel approach

Chattopadhyay¹

2013

IJBET

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This paper is a novel attempt to model a perception process in the diagnosis of depression. In order to do so, two Fuzzy Clustering Techniques (FCT), such as Fuzzy C-means (FCM) and Fuzzy k-Nearest Neighbour (FkNN) are applied. Both the techniques have a special parameter called as 'cluster fuzzifier' (m), which determines the degree of fuzziness between any two clusters. Hence, by varying 'm', one can manipulate the partition between the clusters. Thus, appropriate tuning of 'm' is critical to obtain the desired number of good quality clusters. The paper proposes that 'm' mathematically mimics doctors' diagnostic perceptions, which needs to be tuned appropriately for making a correct diagnosis, i.e. assigning appropriate class labels of depression. Having proposed this, the paper examines how 'm' influences the clustering task, on a sample of real-world depression cases.

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“…A CBR system has been developed to effectively screen hyperactive attention deficit disorder in both children and adults (Brien et al ., ). Hierarchical tree‐based fuzzy model has also been tried with success to classify ‘borderline’ PMS (Chattopadhyay & Acharya, ). In another study, the shortfall of CBR system, that is, its inability in assigning optimum weights to the attributes, has been tackled by combining it with the genetic algorithm (Ahn & Kim, ).…”

Section: Aims and Objectives Of The Studymentioning

confidence: 99%

A Case‐Based Reasoning system for complex medical diagnosis

et al. 2012

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A Case‐Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR‐based expert system that uses the K‐nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto‐set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu‐driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real‐world PMS cases.

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A Novel Mathematical Approach to Diagnose Premenstrual Syndrome

Cited by 16 publications

References 22 publications

The relationship between premenstrual syndrome and the quality of sleep among Egyptian women: an observational study

The relationship between premenstrual syndrome and the quality of sleep among Egyptian women: an observational study

Mathematical modelling of doctors' perceptions in the diagnosis of depression: a novel approach

A Case‐Based Reasoning system for complex medical diagnosis

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