Improving drug repositioning with negative data labeling using large language models by Milan Picard, Mickael Leclercq, Antoine Bodein, Marie Pier Scott-Boyer, Olivier Perin, Arnaud Droit

“…We then applied a machine learning ensemble to this new dataset to assess the repurposing potential of the remaining 11,043 drugs in the DrugBank database. …”
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The early warning paradox by Hugh Logan Ellis, Edward Palmer, James T. Teo, Martin Whyte, Kenneth Rockwood, Zina Ibrahim

“…Machine learning models in healthcare aim to predict critical outcomes but often overlook existing Early Warning Systems’ impact. …”
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Advanced analysis of soil pollution in southwestern Ghana using Variational Autoencoders (VAE) and positive matrix factorization (PMF) by Raymond Webrah Kazapoe, Daniel Kwayisi, Seidu Alidu, Samuel Dzidefo Sagoe, Aliyu Ohiani Umaru, Ebenezer Ebo Yahans Amuah, Millicent Obeng Addai, Obed Fiifi Fynn

“…Integrating chemometric and machine learning techniques provides a dynamic system that can monitor pollution shifts early, to aid remediation efforts in highly affected areas.…”
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Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms by Norhan Khallaf, Osama Abd-El Rouf, Abeer D. Algarni, Mohy Hadhoud, Ahmed Kafafy

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Performance of artificial intelligence on cervical vertebral maturation assessment: a systematic review and meta-analysis by Termeh Sarrafan Sadeghi, Seyed AmirHossein Ourang, Fatemeh Sohrabniya, Soroush Sadr, Parnian Shobeiri, Saeed Reza Motamedian

“…Abstract Background Artificial intelligence (AI) methods, including machine learning and deep learning, are increasingly applied in orthodontics for tasks like assessing skeletal maturity. …”
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Kombinasi Seleksi Fitur Berbasis Filter dan Wrapper Menggunakan Naive Bayes pada Klasifikasi Penyakit Jantung by Siti Roziana Azizah, Rudy Herteno, Andi Farmadi, Dwi Kartini, Irwan Budiman

“…Data yang digunakan dalam penelitian ini adalah data penyakit jantung yang didapatkan dari UCI Machine Learning Repository. Dari implementasi pemodelan yang akan dilakukan menghasilkan nilai akurasi tertinggi sebesar 91.80% pada algoritma Naive Bayes dengan kombinasi union hasil seleksi fitur Information Gain dan Gain Ratio menggunakan perbandingan data latih dan data uji 80:20. …”
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Peningkatan Akurasi Klasifikasi Algoritma C 4.5 Menggunakan Teknik Bagging pada Diagnosis Penyakit Jantung by Erwin Prasetyo, Budi Prasetiyo

“…Data penyakit jantung diambil dari dataset UCI Machine Learning Repository. Tujuan dari penulis melakukan penelitian ini yaitu untuk mengetahui penerapan teknik bagging pada algoritma C4.5, mengetahui hasil akurasi dalam algoritma C4.5, dan membandingkan tingkat akurasi dari penerapan teknik bagging pada algoritma C4.5. …”
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A comprehensive analysis of molecular characteristics of hot and cold tumor of gastric cancer by Chenxi Lv, Tianwei Chen, Jiangtao Li, Yuqiang Shan, Hong Zhou

“…Subsequently, 101 machine learning algorithm combinations were employed to construct a prognostic model based on the identified gene modules. …”
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Analisis Sentimen Wacana Pemindahan Ibu Kota Indonesia Menggunakan Algoritma Support Vector Machine (SVM) by Primandani Arsi, Retno Waluyo

“…Dalam penerapan analisis sentimen menggunakan metode machine learning terdapat beberapa metode yang sering digunakan. …”
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Seleksi Fitur dengan Particle Swarm Optimization pada Klasifikasi Penyakit Parkinson Menggunakan XGBoost by Deni Kurnia, Muhammad Itqan Mazdadi, Dwi Kartini, Radityo Adi Nugroho, Friska Abadi

“…Saat ini diagnosa dapat dilakukan menggunakan machine learning dengan memanfaatkan rekaman suara pasien. …”
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Deteksi Objek menggunakan Dashboard Camera untuk Sistem Peringatan Pencegah Kecelakaan pada Mobil by Raymond Sutjiadi, Timothy John Pattiasina

“…This application was developed using Object Detection Method in Tensorflow Open Source Machine Learning Library. The research stage was started from problem analysis, literature study to search comparison from previous research, also software development and finalized with testing to measure system performance. …”
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Pengembangan Sistem Pemantauan Sentimen Berita Berbahasa Indonesia Berdasarkan Konten dengan Long-Short-Term Memory by Dewi Yanti Liliana, Nadia Nurul Hikmah, Maykada Harjono

“…Sistem pengklasifikasi secara otomatis berbasis machine learning dilakukan dengan membangun model pembelajaran dari korpus berita yang berasal dari situs berita daring. …”
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PREDICTING STOCK PRICE DIRECTION OF EUROZONE BANKS: CAN DEEP LEARNING TECHNIQUES OUTPERFORM TRADITIONAL MODELS? by Bogdan Ionuț ANGHEL

“…The findings suggest that traditional machine learning models are more effective than advanced deep learning models for predicting stock price direction in the Eurozone banking sector. …”
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Method for Creating Domain-Specific Dataset Ontologies from Text in Uncontrolled English by Minab Shokoufeh Salem, Nazaruka Erika

“…The prominent technologies for implementation of the proposed method are machine learning, including classification algorithms and natural language processing using a large language model. …”
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Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction by Joon Yul Choi, Doo Eun Kim, Sung Jin Kim, Hannuy Choi, Tae Keun Yoo

“…ChatGPT-4 effectively analyzed ocular data, calculated key indicators, generated calculator codes, and outperformed traditional machine learning models and indicators in handling unstructured data and corneal topography. …”
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Short-term power consumption forecasting using neural networks with first- and second-order differencing by Meftah Elsaraiti

“…Recent advancements in machine learning, particularly long short-term memory (LSTM) networks, have addressed some of these limitations by leveraging neural network architectures capable of learning complex temporal dependencies. …”
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Southeast Australia encapsulates the recent decade of extreme global weather and climate events by Milton Speer, Lance Leslie

“…Accelerated GW amplifies the impacts of SEAUS climate drivers, depending on their phases. We used machine learning attribution to identify climate drivers responsible for a range of extreme events. …”
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Sentiment Analysis Twitter Bahasa Indonesia Berbasis WORD2VEC Menggunakan Deep Convolutional Neural Network by Hans Juwiantho, Esther Irawati Setiawan, Joan Santoso, Mauridhi Hery Purnomo

“…Penggunaan metode classical machine learning yang sudah banyak diterapkan pada sentiment analysis, tetapi metode tersebut tidak memperhatikan pentingnya urutan kata pada suatu kalimat. …”
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Enhancing Semi-Supervised Learning With Concept Drift Detection and Self-Training: A Study on Classifier Diversity and Performance by Jose L. M. Perez, Roberto S. M. Barros, Silas G. T. C. Santos

“…Machine learning algorithms that assist in decision-making are becoming crucial in several areas, such as healthcare, finance, marketing, etc. …”
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Klasifikasi Ulasan Palsu Menggunakan Borderline Over Sampling (BOS) dan Support Vector Machine (SVM) (Studi Kasus : Ulasan Tempat Makan) by Aisyah Awalina, Fitra Abdurrachman Bachtiar, Indriati Indriati

“…Ulasan palsu bisa secara efektif dibedakan menggunakan machine learning. Namun, banyak dari dataset ulasan palsu ini tidak seimbang (imbalanced dataset) sehingga dapat mempengaruhi hasil klasifikasi. …”
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