A Hybrid Deep Learning and Natural Language Processing Model for Plant Ubiquitination Sites Prediction DOI

Thi-Xuan Tran,

Thi-Tuyen Nguyen,

Nguyen Quoc Khanh Le

и другие.

Lecture notes in networks and systems, Год журнала: 2025, Номер unknown, С. 455 - 465

Опубликована: Янв. 1, 2025

Язык: Английский

Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine DOI Creative Commons
Dolores R. Serrano,

Francis C. Luciano,

Brayan J. Anaya

и другие.

Pharmaceutics, Год журнала: 2024, Номер 16(10), С. 1328 - 1328

Опубликована: Окт. 14, 2024

Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep and other advanced computational methods. These innovations unlocked unprecedented opportunities the acceleration drug discovery delivery, optimization treatment regimens, improvement patient outcomes. AI is swiftly transforming industry, revolutionizing everything from development to personalized medicine, target identification validation, selection excipients, prediction synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While integration promises enhance efficiency, reduce costs, improve both medicines health, it also raises important questions regulatory point view. In this review article, we will present comprehensive overview AI's applications in covering areas such as discovery, safety, more. By analyzing current research trends case studies, aim shed light on transformative impact industry its broader implications healthcare.

Язык: Английский

Процитировано

42
Machine Learning Assisted Bithiophene Based Donor Acceptor Selection to Design New Fluoresent Dyes for Photovoltaic Applications DOI
Sadaf Noreen, Sajjad Hussain Sumrra,

Abrar U. Hassan

и другие.

Journal of Fluorescence, Год журнала: 2025, Номер unknown

Опубликована: Янв. 11, 2025

Язык: Английский

Процитировано

2
A fast and efficient machine learning assisted prediction of urea and its derivatives to screen crystal propensity with experimental validation DOI
Cihat Güleryüz, Sajjad Hussain Sumrra,

Abrar U. Hassan

и другие.

Materials Today Communications, Год журнала: 2025, Номер unknown, С. 111692 - 111692

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1
A Hybrid Deep Learning and Natural Language Processing Model for Plant Ubiquitination Sites Prediction DOI

Thi-Xuan Tran,

Thi-Tuyen Nguyen,

Nguyen Quoc Khanh Le

и другие.

Lecture notes in networks and systems, Год журнала: 2025, Номер unknown, С. 455 - 465

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0