Research

As the national university, we champion and support innovative research that addresses the country’s most pressing challenges.

26 Mar 2026

Researchers achieve an 86% response accuracy rate for a hand orthosis for stroke rehabilitation, using surface electromyography signals

Loss of control in gripping with the hand is a possible long-term effect of stroke. Recovery from this is possible...

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25 Mar 2026

Philippine island communities face unique healthcare challenges shaped by geographical isolation and disparities in technological access and literacy

In regions separated by water and challenging terrain, the healthcare journey involves not only crossing physical distances but also navigating...

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24 Mar 2026

The Spanish and Tausug versions of the landmark Sulu–Spanish Treaty of 1836 reflect different intentions

In the second half of the 1830s, several indigenous overlords in the Sulu–Mindanao–Borneo region began signing treaties, marking a new...

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20 Mar 2026

Scientists create the first draft genome of the endangered Visayan spotted deer, a species found only in the Philippines

The genus Rusa, native to South and Southeast Asia, lives in diverse habitats ranging from dense forests to grasslands. Among its...

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19 Mar 2026

A comprehensive study on the health and nutrition of older Filipino adults highlights the need for tailored interventions

Several local studies have been conducted among community-dwelling older Filipinos; however, data gaps in nutrition research exist. In particular, there...

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18 Mar 2026

Libraries not only promote discourse but are also subjects of discourse themselves

In the past, libraries primarily served as channels for disseminating discourse through books, magazines, newspapers, and other important documents. Today,...

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17 Mar 2026

A two-stage symptom detection model was developed to more accurately identify depression signs in social media posts

Depression is a health condition characterized by changes in mood, cognition, and behavior. According to the World Health Organization (WHO),...

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16 Mar 2026

E-cigarettes may have less impact on the development of tooth decay and periodontal disease than traditional cigarettes

Cigarette smoking is a known risk factor for numerous health problems, including respiratory infections and cancers. It is also associated...

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13 Mar 2026

“Halata” can now be used to refer to gay men who act straight, showing how the definition of kabaklaan in the Philippines is ever-changing

In the Philippines, representation of gays has long been dichotomous. There is the bakla, depicted as flamboyant, effeminate and low...

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10 Mar 2026

Study develops a baseline econometric model to estimate potential hydrogen demand in Tarlac and explore hydrogen as an alternative energy source

This study aims to establish a baseline econometric model to inform the possible development of green hydrogen production in Tarlac....

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09 Mar 2026

There is significant spatial clustering of traffic accident locations in Quezon City

The surge in urban vehicular traffic volume over the past decade has resulted in a rise in the occurrence of...

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06 Mar 2026

Taken together, the oral narratives of families left behind by Duterte’s drug war reveal a shared understanding of political struggle and resistance

Former Philippine President Rodrigo Duterte is infamous for his war on drugs campaign, commonly known as Oplan Tokhang, which killed...

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Research

Skin cancer is one of the most common and dangerous cancers globally, but early detection can significantly reduce mortality rates. Dermatologists distinguish between benign and malignant lesions that often look very similar in shape, border, and color, even though both come from melanocyte cells. This makes diagnosis challenging. Typically, doctors use dermatoscopes to examine skin lesions and may perform biopsies to confirm a diagnosis. Expert dermatologists can diagnose melanoma with over 60% accuracy even without specialized visual aids.

Recent advancements in technology have shown that deep learning systems can match dermatologists’ accuracy in identifying skin cancer. However, there is still no universally reliable method for automated diagnosis. This study aims to develop a novel deep-learning approach for automatically predicting the type of skin lesion, providing doctors with a supportive tool for evaluating lesion images. The proposed model also incorporates patient characteristics—such as lesion anatomical location, age, and gender—to improve prediction accuracy. Recent findings indicate that men are 4% more likely to die from melanoma and 10% more likely to develop the disease than women.

Our research focuses on enhancing skin cancer detection by developing advanced Convolutional Neural Network (CNN) models and hybrid machine learning techniques. We tested four different CNN variations and combined them with methods like Support Vector Machines, Random Forest, and Logistic Regression. Our models achieved high accuracy rates of up to 99% when analyzing over 10,000 images from the HAM10000 dataset. We also used techniques to balance and normalize the data, making the models more effective. Importantly, our findings suggest that incorporating patient information with lesion images can further improve diagnostic accuracy. This work is pivotal in advancing automated
tools for diagnosing skin cancer, making early detection more reliable, and potentially saving lives through timely medical treatment and intervention.

Authors: Hadeel Alharbi (College of Computer Science and Engineering, University of Hail), Gabriel Avelino Sampedro (Department of Computer Science, University of the Philippines Diliman), Roben A. Juanatas (College of Computing and Information Technologies, National University, Manila) and Se-jug Lim (School of Electrical and Computer Engineering, Yeosu Campus, Chonnam National University)

Read the full paper: https://doi.org/10.3389/fmed.2024.1495576