The Clinical Course of Primary Recurrent Depression in Pharmacologically Treated Female Patients

1975 ◽  
Vol 126 (4) ◽  
pp. 336-345 ◽  
Author(s):  
Tamara Kolakowska
Keyword(s):  
Clinical Studies ◽  
Clinical Course ◽  
Depressive Illness ◽  
Recurrent Depression ◽  
Female Patients ◽  
Affective Illness ◽  
Diagnosis And Classification ◽  
The Many

The main questions of diagnosis and classification of depressive illness put forward by Sir Aubrey Lewis in the 30's are still under discussion. Despite the many published clinical studies of affective illness, there remain—as recently stressed by Klerman (1971)—problems requiring further description and investigation.

Recent Advances in the Genetics of Affective Illness

1981 ◽  
Vol 15 (3) ◽  
pp. 239-242 ◽  
Author(s):  
Norman McI. James
Keyword(s):  
Hla Antigens ◽  
Mendelian Inheritance ◽  
Depressive Illness ◽  
Bipolar Illness ◽  
Affective Illness ◽  
The Past ◽  
Bipolar Patients ◽  
Morbidity Risk ◽  
Physiological Markers

Variability in the classification of depressive illness greatly handicapped the work of geneticists prior to the application of the polarity concept. The past decade has however, seen a burgeoning of interest in this area, with researchers concentrating on bipolar illness, this being the most clearly defined entity. Findings of a lifetime morbidity risk for affective illness of 15–20% in the first degree relatives of bipolar patients has been usual. This compares with 10–15% for patients with unipolar illness. Transmission patterns indicative of known forms of Mendelian inheritance have not been consistently demonstrated. Genetic markers including colour blindness and HLA antigens have been pursued avidly but have yielded inconclusive results. Further progress seems unlikely unless more sub-groups are defined using biochemical and physiological markers.

Effectiveness of Supervised Classification Models for Hate Speech on Twitter

2020 ◽  
Author(s):  
Kunal Srivastava ◽  
Ryan Tabrizi ◽  
Ayaan Rahim ◽  
Lauryn Nakamitsu
Keyword(s):  
Supervised Classification ◽  
Hate Speech ◽  
The Internet ◽  
Classification Models ◽  
Personal Attack ◽  
Political Beliefs ◽  
The Many ◽  
Primary Medium ◽  
Offensive Speech

<div> <div> <div> <p>Abstract </p> <p>The ceaseless connectivity imposed by the internet has made many vulnerable to offensive comments, be it their physical appearance, political beliefs, or religion. Some define hate speech as any kind of personal attack on one’s identity or beliefs. Of the many sites that grant the ability to spread such offensive speech, Twitter has arguably become the primary medium for individuals and groups to spread these hurtful comments. Such comments typically fail to be detected by Twitter’s anti-hate system and can linger online for hours before finally being taken down. Through sentiment analysis, this algorithm is able to distinguish hate speech effectively through the classification of sentiment. </p> </div> </div> </div>

Breast Cancer Detection and Classification using Traditional Computer Vision Techniques: A Comprehensive Review

2020 ◽  
Vol 16 ◽  
Author(s):  
Saliha Zahoor ◽  
Ikram Ullah Lali ◽  
Muhammad Attique Khan ◽  
Kashif Javed ◽  
Waqar Mehmood
Keyword(s):  
Breast Cancer ◽  
Computer Aided Diagnosis ◽  
Diagnose Breast Cancer ◽  
Initial Stage ◽  
Computer Aided ◽  
Diagnosis And Classification ◽  
And Performance ◽  
Tools And Techniques ◽  
Aided Diagnosis

: Breast Cancer is a common dangerous disease for women. In the world, many women died due to Breast cancer. However, in the initial stage, the diagnosis of breast cancer can save women's life. To diagnose cancer in the breast tissues there are several techniques and methods. The image processing, machine learning and deep learning methods and techniques are presented in this paper to diagnose the breast cancer. This work will be helpful to adopt better choices and reliable methods to diagnose breast cancer in an initial stage to survive the women's life. To detect the breast masses, microcalcifications, malignant cells the different techniques are used in the Computer-Aided Diagnosis (CAD) systems phases like preprocessing, segmentation, feature extraction, and classification. We have been reported a detailed analysis of different techniques or methods with their usage and performance measurement. From the reported results, it is concluded that for the survival of women’s life it is essential to improve the methods or techniques to diagnose breast cancer at an initial stage by improving the results of the Computer-Aided Diagnosis systems. Furthermore, segmentation and classification phases are challenging for researchers for the diagnosis of breast cancer accurately. Therefore, more advanced tools and techniques are still essential for the accurate diagnosis and classification of breast cancer.

Depression

2017 ◽  
Author(s):  
Philip Cowen
Keyword(s):  
International Classification Of Diseases ◽  
Behavioural Therapy ◽  
Historical Background ◽  
Cognitive Behavioural ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
Diagnosis And Classification ◽  
Modern Experience ◽  
Symptoms And Signs

This chapter discusses the symptomatology, diagnosis, and classification of depression. It begins with a brief historical background on depression, tracing its origins to the classical term ‘melancholia’ that describes symptoms and signs now associated with modern concepts of the condition. It then considers the phenomenology of the modern experience of depression, its diagnosis in the operational scheme of ICD-10 (International Classification of Diseases, tenth edition), and current classificatory schemes. It looks at the symptoms needed to meet the criteria for ‘depressive episode’ in ICD-10, as well as clinical features of depression with ‘melancholic’ features or ‘somatic depression’ in ICD-10. It also presents an outline of the clinical assessment of an episode of depression before concluding with an overview of issues that need to be taken into account when addressing approaches to treatment, including cognitive behavioural therapy and the administration of antidepressants.

Future Directions

2020 ◽  
pp. 476-479
Author(s):  
Marc N. Potenza ◽  
Kyle A. Faust ◽  
David Faust
Keyword(s):  
Technology Development ◽  
Digital Technologies ◽  
World Health ◽  
International Classification Of Disease ◽  
Levels Of Use ◽  
Pornography Use ◽  
Negative Impacts ◽  
Mental Health Treatments ◽  
The Many

As digital technology development continues to expand, both its positive and negative applications have also grown. As such, it is essential to continue gathering data on the many types of digital technologies, their overall effects, and their impact on public health. The World Health Organization’s inclusion of Gaming Disorder in the eleventh edition of the International Classification of Disease (ICD-11) indicates that some of the problematic effects of gaming are similar to those of substance-use disorders and gambling. Certain behaviors easily engaged in via the internet may also lead to compulsive levels of use in certain users, such as shopping or pornography use. In contrast, digital technologies can also lead to improvements in and wider accessibility to mental health treatments. Furthermore, various types of digital technologies can also lead to benefits such as increased productivity or social functioning. By more effectively understanding the impacts of all types of digital technologies, we can aim to maximize their benefits while minimizing or preventing their negative impacts.

Diagnoses, Dimensions, and DSM-5

2010 ◽  
pp. 254-279
Author(s):  
Thomas A. Widiger ◽  
Maryanne Edmundson
Keyword(s):  
Substance Use ◽  
Mental Disorders ◽  
Paradigm Shift ◽  
Empirical Support ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Dimensional Classification ◽  
Diagnosis And Classification

The Diagnostic and Statistical Manual of Mental Disorders, Third Edition (DSM-III) is often said to have provided a significant paradigm shift in how psychopathology is diagnosed. The authors of DSM-5 have the empirical support and the opportunity to lead the field of psychiatry to a comparably bold new future in diagnosis and classification. The purpose of this chapter is to address the validity of the categorical and dimensional models for the classification and diagnosis of psychopathology. Considered in particular will be research concerning substance use disorders, mood disorders, and personality disorders. Limitations and concerns with respect to a dimensional classification of psychopathology are also considered. The chapter concludes with a recommendation for a conversion to a more quantitative, dimensional classification of psychopathology.

Conditioning and Sensitisation in the Longitudinal Course of Affective Illness

1986 ◽  
Vol 149 (2) ◽  
pp. 191-201 ◽  
Author(s):  
Robert M. Post ◽  
David R. Rubinow ◽  
James C. Ballenger
Keyword(s):  
Depressive Illness ◽  
Manic Depressive Illness ◽  
Conceptual Approach ◽  
Longitudinal Course ◽  
Behavioural Sensitisation ◽  
Affective Illness ◽  
Biological Variables ◽  
Manic Depressive ◽  
Progressive Course

Few biological theories of manic-depressive illness have focused on the longitudinal course of affective dysfunction and the mechanisms underlying its often recurrent and progressive course. The authors discuss two models for the development of progressive behavioural dysfunction—behavioural sensitisation and electrophysiological kindling—as they provide clues to important clinical and biological variables relevant to sensitisation in affective illness. The role of environmental context and conditioning in mediating behavioural and biochemical aspects of this sensitisation is emphasised. The sensitisation models provide a conceptual approach to previously inexplicable clinical phenomena in the longitudinal course of affective illness and may provide a bridge between psychoanalytic/psychosocial and neurobiological formulations of manic-depressive illness.

scholarly journals Panniculitis in Children

2021 ◽  
Vol 8 (3) ◽  
pp. 315-336
Author(s):  
Isabelle Moulonguet ◽  
Sylvie Fraitag
Keyword(s):  
Clinical Presentation ◽  
Inflammatory Diseases ◽  
Secondary Process ◽  
Immune Disorders ◽  
Lesion Site ◽  
Heterogenous Group ◽  
Systemic Disorder ◽  
Diagnosis And Classification ◽  
Subcutaneous Adipose

Panniculitides form a heterogenous group of inflammatory diseases that involve the subcutaneous adipose tissue. These disorders are rare in children and have many aetiologies. As in adults, the panniculitis can be the primary process in a systemic disorder or a secondary process that results from infection, trauma or exposure to medication. Some types of panniculitis are seen more commonly or exclusively in children, and several new entities have been described in recent years. Most types of panniculitis have the same clinical presentation (regardless of the aetiology), with tender, erythematous subcutaneous nodules. Although the patient’s age and the lesion site provide information, a histopathological assessment is sometimes required for a definitive diagnosis and classification of the disorder. In children, most panniculitides are lobular. At present, autoimmune inflammatory diseases and primary immunodeficiencies have been better characterised; panniculitis can be the presenting symptom in some of these settings. Unexplained panniculitis in a young child should prompt a detailed screen for monogenic immune disorders because the latter usually manifest themselves early in life. Here, we review forms of panniculitis that occur primarily in children, with a focus on newly described entities.

Sign in / Sign up

Export Citation Format

Share Document