Hybrid of Deep Feature Extraction and Machine Learning Ensembles for Imbalanced Skin Cancer Datasets.

Skin cancer remains one of the most common and deadly forms of cancer, necessitating accurate and early diagnosis to improve patient outcomes. In order to improve classification performance on unbalanced datasets, this study proposes a distinctive approach for classifying skin cancer that utilises both machine learning (ML) and deep learning (DL) methods. We extract features from three different DL models (DenseNet201, Xception, Mobilenet) and concatenate them to create an extensive feature set.

Establishing Normative Values of Peak Expiratory Flow Rates in the Paediatric Population in Jharkhand.

Background The peak expiratory flow rate (PEFR) is the maximum flow rate (expressed as L/s) generated during a forceful exhalation, starting from full inspiration. It is an effort-dependent parameter and reflects large airway flow. It depends on lung recoil, muscular strength of patients, and voluntary effort.

Assessment of Symptoms Associated with Temporomandibular Dysfunction and Bruxism among Elderly Population: An Epidemiological Survey.

Aim: The aim of the study was to assess the symptoms associated with temporomandibular disorders (TMD) and bruxism among elderly population in Ranchi, India.

Materials And Methods: A cross-sectional study was done on 600 elderly subjects; data regarding the signs and symptoms associated with temporomandibular disorder and bruxism were recorded using both structured questionnaire and clinical examination. Spearman correlation analysis was done to find the association between TMD and bruxism.

Clinical Success of Screw-retained Dental Implants: A Systematic Review.

Objective: The objective of the research was to review the literature on clinical evaluation and success of screw-retained dental implants by assessing the marginal bone loss (MBL).

Methods: Online electronic databases such as PubMed/MEDLINE, Google Scholar, and Cochrane Library were searched using appropriate keywords for the last 20 years, dated from January 1, 2000, till August 1, 2021, with a restriction on language. Additional sources like major journals, unpublished studies, conference proceedings, and cross-references were explored.

Fast and memory efficient approach for mapping NGS reads to a reference genome.

New generation sequencing machines: Illumina and Solexa can generate millions of short reads from a given genome sequence on a single run. Alignment of these reads to a reference genome is a core step in Next-generation sequencing data analysis such as genetic variation and genome re-sequencing etc. Therefore there is a need of a new approach, efficient with respect to memory as well as time to align these enormous reads with the reference genome.

WBFQC: A new approach for compressing next-generation sequencing data splitting into homogeneous streams.

Genomic data nowadays is playing a vital role in number of fields such as personalized medicine, forensic, drug discovery, sequence alignment and agriculture, etc. With the advancements and reduction in the cost of next-generation sequencing (NGS) technology, these data are growing exponentially. NGS data are being generated more rapidly than they could be significantly analyzed.