Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

Cadmium sulfide and Aluminum doped CdS thin films were prepared by thermal evaporation technique in vacuum on a heated glass substrates at 373K. A comparison between the optical properties of the pure and doped films was made through measuring and analyzing the transmittance curves, and the effect of the annealing temperature on these properties were estimated. All the films were found to exhibit high transmittance in the visible/ near infrared region from 500nm to 1100nm.The optical band gap energy was found to be in the range 2.68-2.60 eV and 2.65-2.44 eV for CdS and CdS:Al respectively , with changing the annealing temperature from room temperature to 423K.Optical constants such as refractive index, extinction coefficient, and complex di

In the present work, pulsed laser deposition (PLD) technique was applied to a pellet of Chromium Oxide (99.999% pure) with 2.5 cm diameter and 3 mm thickness at a pressure of 5 Tons using a Hydraulic piston. The films were deposited using Nd: YAG laser λ= (4664) nm at 600 mJ and 400 number of shot on a glass substrate, The thickness of the film was (107 nm). Structural and morphological analysis showed that the films started to crystallize at annealing temperature greater than 400 oC. Absorbance and transmittance spectra were recorded in the wavelength range (300-
4400) nm before and after annealing. The effects of annealing temperature on absorption coefficient, refractive index, extinction coefficient, real and imaginary parts of d

Effect of the thermal annealing at 400oC for 2 hours and Argon laser radiation for half hour on the optical properties of AgAlS2 thin films, prepared on glass slides by chemical spray pyrolysis at 360oC with (0.18±0.05) μm thickness .The optical characteristics of the prepared thin films have been investigated by UV/Vis spectrophotometer in the wavelength range (300 – 1100)nm .The films have a direct allow electronic transition with optical energy (Eg) values decreased from (2.25) eV for untreated thin films to (2.10) eV for the annealed films and to (2.00) eV for the radiated films. The maximum value of the refractive index (n) for all thin films are given about (2.6). Also the extinction coefficient (K) and the real and imaginary d

SnS has been widely used in photoelectric devices due to its special band gap of 1.2-1.5 eV. Here, we reported on the fabrication of SnS nanosheets and the effect of synthesis condition together with heat treatment on its physical properties. The obtained band gap of the SnS nanosheets is in the rage of 1.37-1.41 eV. It was found that the photo-current density of a thin film comprised of SnS nanosheets could be enhanced significantly by annealing treatment. The maximum photo-current density of the stack structure of FTO/SnS/CdS/Pt was high as 389.5 mu A cm(-2), rendering its potential application in high efficiency solar hydrogen production.

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed