Predicting depression in Bangladeshi undergraduates using machine learning

Predicting depression in Bangladeshi undergraduates using machine learning

Afficher d'autres versions (1)

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Détails bibliographiques
Auteurs principaux:	Choudhury, Ahnaf Atef, Khan, Md Rezwan Hassan, Nahim, Nabuat Zaman, Tulon, Sadid Rafsun
Autres auteurs:	Chakrabarty, Amitabha
Format:	Thèse
Langue:	English
Publié:	BRAC University 2019
Sujets:	Depression Undergraduates Machine learning Data mining
Accès en ligne:	http://hdl.handle.net/10361/11470

Documents similaires

Predicting depression in Bangladeshi undergraduates using machine learning
par: Choudhury, Ahnaf Atef, et autres
Publié: (2019)

A machine learning approach to detect depression and anxiety using supervised learning
par: Ullas, Md Tahmidur Rahman, et autres
Publié: (2019)

Prediction of anxiety and depression among the transgender in Bangladesh
par: Easha, Ishrat Jahan, et autres
Publié: (2023)

Determination of severity of postpartum depression in Bangladeshi women
par: Islam, Shanta
Publié: (2018)

BMI perception of undergraduate students on caffeine intake, smoking and physical exercise
par: Shorna, Fatema
Publié: (2021)

Mayo Clinic on depression /
Publié: (2001)

Depression: a major global concern?
par: Samiullah, Md.
Publié: (2018)

Machine learning for stress prediction
par: Salehin, Sherajus, et autres
Publié: (2023)

Saffron in treating depression in women- a review
par: Ibrahim, Sumaiya Binte
Publié: (2024)

A review on major depressive disorder
par: Sadia, Mumtahina
Publié: (2024)

A Review on Saffron in the Treatment of Depression in Women
par: Shifa, Farhana Akter
Publié: (2024)

Fighting depression: psychological approaches among Bangladeshi university students
par: Sen, Sanjib Kumar, et autres
Publié: (2022)

An experiential investigation on internet addiction and specific disorders like depression, self-esteem and introversion among university students
par: Rubaiyat, Nadia, et autres
Publié: (2019)

Gut microbiota and depression: insights into the probable link between the two
par: Momo, Sayma Hossain
Publié: (2024)

Stock price prediction
par: Das, Kaushik, et autres
Publié: (2023)

Detection of fake identities on twitter using supervised machine learning
par: Rahman, MD. Takiur, et autres
Publié: (2019)

Culture and depression : studies in the anthropology and cross-cultural psychiatry of affect and disorder /
Publié: (1985)

Detecting self-esteem level and depressive indication due to different parenting style using supervised learning techniques
par: Al Taawab, Abdullah, et autres
Publié: (2022)

A machine learning approach to credit default prediction and Individual credit scoring
par: Rahman, Md. Jaber, et autres
Publié: (2018)

Utilization of machine learning classifiers to predict different forms of mental illness: schizophrenia, PTSD, bipolar disorder and depression
par: Jaman, Ayman Ibn, et autres
Publié: (2021)

A computational approach to find alternative drugs for managing depression
par: Mubashira, Musharrat Shaheed
Publié: (2022)

Predicting criminal activities analyzing video signal using machine learning
par: Sadman, Syed Md., et autres
Publié: (2021)

Releasing children from depression : a handbook for elementary teachers and consultants /
par: Butler, Lenora F. (Lenora Frances), 1943-
Publié: (1980)

Prevalence and associated factors of depression among adolescent boys and girls in Bangladesh: Findings from a nationwide survey
par: Mridha, Malay Kanti, et autres
Publié: (2022)

Working in groups outside the classroom: affective challenges and probable solutions
par: Ferdous, Tanjila, et autres
Publié: (2019)

Investigation of in vivo antidiabetic, analgesic, and CNS depressant properties of Lagerstroemia thorelli leaf extract
par: Rajib, Raisha
Publié: (2024)

In vivo evaluation of CNS depressant and antinociceptive activities of different extracts of trewia polycarpa leaves
par: Akter, Nahid
Publié: (2015)

Beyond words: an exploration of free-hand sketches and EEG-based neurobiological signatures to unveil the underlying depression among cancer patients
par: Miami, Anika Tahsin, et autres
Publié: (2023)

Risk factors and consequences of maternal perinatal depressive and anxiety symptoms : a community-based study in rural Bangladesh /
par: Nasreen, Hashima-E
Publié: (2011)

Antioxidant, analgesic and CNS depressant effects of Synedrella nodiflora
par: Nahar, Laizuman,, et autres
Publié: (2016)

Detecting Adverse Drug Reaction (ADR) with data mining and predicting its intensity with machine learning
par: Hussain, Nadib, et autres
Publié: (2018)

Machine learning as an indicator for breast cancer prediction
par: Shadman, Tahsin Mohammed, et autres
Publié: (2019)

Heart disease prediction using machine learning algorithms
par: Ali, Musfiq, et autres
Publié: (2019)

Detecting propagandistic poster title: a machine learning approach
par: Mahmood, Riaz, et autres
Publié: (2024)

Approaching (almost) any Machine learning problem /
par: Thakur, Abhishek
Publié: (2020)

Central nervous system depressant, analgesic and antidiarrheal effects of the seed extracts of Dimocarpus longan lour in rats
par: Ripa, Farhana Alam, et autres
Publié: (2016)

CNS Depressant Activity of Various Parts of Heritiera fomes
par: Taslim, Umiya
Publié: (2022)

Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning
par: Saleque, Shahriar, et autres
Publié: (2021)

Reflection of mental illness and female depression in the works of Sylvia Plath
par: Chowdhury, Samiha Tasfia
Publié: (2024)

Aspect based opinion mining on restaurant reviews
par: Tonmoy, Sazid Hasan, et autres
Publié: (2024)