Zafar Amna, Akram Beenish Ayesha, Wasim Muhammad, Pires Ivan Miguel, Coelho Paulo Jorge
Department of Computer Science, University of Engineering and Technology, Lahore, Pakistan.
Department of Computer Engineering, University of Engineering and Technology, Lahore, Pakistan.
Data Brief. 2025 May 7;60:111621. doi: 10.1016/j.dib.2025.111621. eCollection 2025 Jun.
Perinatal depression (PND) represents a multifaceted mental health issue that impacts women throughout the perinatal period. Existing datasets have a class imbalance issue, resulting in biased outcomes. In Pakistan, we developed a novel dataset called PERI_DEP. This dataset leverages the Patient Health Questionnaire (PHQ-9), Edinburgh Postnatal Depression Scale (EPDS), and socio-demographic questionnaires to gather information about mental health state and socioeconomic details of women participants in urban and rural areas. Our novel PERI_DEP dataset contains 14,008 samples, and women from Lahore and Gujranwala participated. To tackle the issue of class imbalance, we employed Generative Adversarial Network (GAN) oversampling technique on our data. A key insight derived from this dataset is the comparative socio-demographic divide of women in rural and urban areas of Pakistan. PERI_DEP dataset enhances hospital capabilities by streamlining screening processes, customizing interventions, and enabling researchers to identify risk factors and develop new treatments accurately.
围产期抑郁症（PND）是一个多方面的心理健康问题，会影响整个围产期的女性。现有数据集存在类别不平衡问题，导致结果有偏差。在巴基斯坦，我们开发了一个名为PERI_DEP的新数据集。该数据集利用患者健康问卷（PHQ - 9）、爱丁堡产后抑郁量表（EPDS）以及社会人口统计学问卷，来收集有关城乡地区女性参与者心理健康状况和社会经济细节的信息。我们全新的PERI_DEP数据集包含14008个样本，来自拉合尔和古吉兰瓦拉的女性参与其中。为了解决类别不平衡问题，我们对数据采用了生成对抗网络（GAN）过采样技术。从这个数据集得出的一个关键见解是巴基斯坦城乡地区女性在社会人口统计学方面的比较差异。PERI_DEP数据集通过简化筛查流程、定制干预措施以及使研究人员能够准确识别风险因素并开发新的治疗方法，增强了医院的能力。
