Thus far, the most common cause of death in the world is cancer. It consists of abnormally expanding areas that are threatening to human survival. Hence, the timely detection of cancer is important to expanding the survival rate of patients. In this survey, we analyze the state-of-the-art approaches for multi-organ cancer detection, segmentation, and classification. This article promptly reviews the present-day works in the breast, brain, lung, and skin cancer domain. Afterwards, we analytically compared the existing approaches to provide insight into the ongoing trends and future challenges. This review also provides an objective description of widely employed imaging techniques, imaging modality, gold standard database, and related literature on each cancer in 2016–2021. The main goal is to systematically examine the cancer diagnosis systems for multi-organs of the human body as mentioned. Our critical survey analysis reveals that greater than 70% of deep learning researchers attain promising results with CNN-based approaches for the early diagnosis of multi-organ cancer. This survey includes the extensive discussion part along with current research challenges, possible solutions, and prospects. This research will endow novice researchers with valuable information to deepen their knowledge and also provide the room to develop new robust computer-aid diagnosis systems, which assist health professionals in bridging the gap between rapid diagnosis and treatment planning for cancer patients.

This study describes the preparation of graphitic carbon nitride (g-C₃N₄), hematite (α-Fe₂O₃), and their g-C₃N₄/α-Fe₂O₃ heterostructure for the photocatalytic removal of methyl orange (MO) under visible light illumination. The facile hydrothermal approach was utilized for the preparation of the nanomaterials. Powder X-ray diffraction (XRD), Scanning electron microscopy (SEM), Energy dispersive X-ray (EDX), and Brunauer–Emmett–Teller (BET) were carried out to study the physiochemical and optoelectronic properties of all the synthesized photocatalysts. Based on the X-ray photoelectron spectroscopy (XPS) and UV-visible diffuse reflectance (DRS) results, an energy level diagram vs. SHE was established. The acquired results indicated that the nanocomposite exhibited a type-II heterojunction and degraded the MO dye by 97%. The degradation ability of the nanocomposite was higher than that of pristine g-C₃N₄ (41%) and α-Fe₂O₃ (30%) photocatalysts under 300 min of light irradiation. The formation of a type-II heterostructure with desirable band alignment and band edge positions for efficient interfacial charge carrier separation along with a larger specific surface area was collectively responsible for the higher photocatalytic efficiency of the g-C₃N₄/α-Fe₂O₃ nanocomposite. The mechanism of the nanocomposite was also studied through results obtained from UV-vis and XPS analyses. A reactive species trapping experiment confirmed the involvement of the superoxide radical anion (O₂^•−) as the key reactive oxygen species for MO removal. The degradation kinetics were also monitored, and the reaction was observed to be pseudo-first order. Moreover, the sustainability of the photocatalyst was also investigated.